Wageningen University - Department of Social Sciences
MSc Thesis Chair Group Research Methodology
Cross-cultural differences in
the effect of number of
response categories on Locus
of Control
August 2015
MSc Programme:
Name of student:
Master Management, Economics Lisette Feijen
And Consumer Studies
Specialisation:
Name of Supervisor:
Health and Society
Ruud Zaalberg
Thesis code:
YRM-80333
Copyright © 2015 All rights reserved. No part of this publication may be reproduced or distributed in
any form or by any means, without the prior consent of the author(s). This report is produced by a
student of Wageningen University, as part of her MSc. programme. It is not an official publication of
Wageningen University or Wageningen UR and the content herein does not represent any formal
position or representation by Wageningen University.
2
Master Thesis - Lisette Feijen
Cross-cultural differences in the effect
of number of response categories on
Locus of Control
MASTER THESIS
Lisette Feijen
| 880325-239-040
DATE
THESIS CODE
| AUGUST 4, 2015
| YRM-80333
CHAIR GROUP
SUPERVISOR
EXAMINER
| RESEARCH METHODOLOGY
| RUUD ZAALBERG
| HILDE TOBI
Master Thesis - Lisette Feijen
3
Preface
A young modern composer said: “you can go to school forever, but you’re never really going to
learn until you just do it” (Michael Giacchino). This quote inspired me to finish my Master’s degree
with this thesis and prepare myself for the work life, by just doing it.
The starting point of the subject was Locus of Control, a concept which is related to my background
of Health and Society. This concept intrigues me because it gives insights on personal attributes of
people and can help to give personal advice. Knowing whether people are independent by
themselves or rely mostly on others will help to give people advice that suits their personality.
In discussing Locus of Control an interesting feature of the phenomena of the scale came up. Not
the scale length (number of items), because this already has been researched, but the number of
response categories. When using a Likert-type scale you can vary the number of response
categories used in order to investigate how many response categories would be most or more
suited. Comparing the number of response categories asks for quantitative analyses, an area of
analyses that is of interest to me. Quantitative methods are more straightforward and are more
clear for interpretation compared to qualitative methods. Also a large number of responses can be
generated.
The subject of Locus of Control and scale aspects give me the opportunity to work on a more
quantitative basis within the field of Health and Society. It also gives me the opportunity to further
develop quantitative data analysis skills. This thesis research enables me to get more knowledge of
and experience in research methodology, which is a generic field and can be applied within different
research domains. This adds to my personal development and future career.
During my thesis I learned a lot from my supervisors and their feedback. I also further developed
my data analysis skills, in which I feel really comfortable. This gave me a direction for my future
career. This thesis and its process made me realize what aspects of the academic world I am most
interested in, namely quantitative data analysis and consultancy. I hope to work with these aspects
during my career.
I would like to conclude with: “life is full of turns which you take at your own speed, as long as you
keep moving and continue on a straight road”.
Master Thesis - Lisette Feijen
5
Acknowledgements
Here I would like to thank some people. First, I would like to thank my supervisors for their guidance.
Ruud Zaalberg, I would like to thank you for your teachings about multivariate quantitative analysis,
our fruitful meetings and the discussions we had. Hilde Tobi, I would like to thank you for your
critical questions and challenges you gave me. These were very good for my development. Second,
I also would like to thank my friends who supported me during my final presentation. Third, I want
to thank my parents for their support during my academic career. Lastly, I want to thank Erik for his
support during the process of my thesis.
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Master Thesis - Lisette Feijen
Summary
The ‘second generation’ of measuring the Locus of Control (LOC) construct uses Likert-type scales.
Many LOC scales have been developed for specific domains and research thus far has focused on
the number of items measuring LOC. There is not sufficient research with regard to the number of
response categories in measuring LOC. Researchers of the LOC construct use 5 to 7 response
categories as a standard. This thesis investigates the influence of a larger number of response
categories, 9-points, on the data structure of LOC. This means that the relative mean and frequency
of extreme scores for Internal Locus of Control (ILOC) and External Locus of Control (ELOC) are
investigated. The association between Internal Locus of Control and External Locus of Control is
also researched. Locus of control can be predicted and moderated by culture, therefore it is
interesting to investigate LOC across cultures. Such a cross-cultural analysis provides insight into
cross-cultural differences in LOC and gives researchers and other professionals tools for
implementation of the LOC construct in practice and input for further research.
A heterogeneous sample is used consisting of students at Wageningen University.
Questionnaires are distributed by teachers, N=500. There are two versions of the questionnaire.
Due to classification of Culture into two dominant cultures (Western vs. Non-Western) there are
nine missing values, leaving N=491. A Principal Axis Factoring is performed to determine the factor
structure (2 correlated factors). Based on this a MANOVA has been conducted with a 2 x 2 x 2
design. Chi-square tests are performed to analyse the frequency of extreme scores (0=no extreme
score, 1=extreme score) and Cochran’s chi-square tests are performed to test for cross-cultural
differences regarding the effect of the number of response categories on the frequency of extreme
scores. Correlation coefficients are used to test the association between Internal Locus of Control
and External Locus of Control.
Results show a significant effect of the number of response categories on the relative mean
and frequency of extreme scores for both ILOC and ELOC. There is no significant effect of culture
nor of version and no significant interaction effects on the relative mean of ILOC and ELOC. There
is a significant effect of culture on the frequency of extreme scores on Internal Locus of Control,
not on External Locus of Control. There are cross-cultural differences regarding the effect of the
number of response categories on the frequency of extreme scores for ILOC and ELOC. Internal
Locus of Control has more extreme scores from the Non-Western culture while External Locus of
Control has more extreme scores from the Western culture. There is no significant (negative)
Master Thesis - Lisette Feijen
7
correlation between ILOC and ELOC in the whole sample. There is a significant negative correlation
between ILOC and ELOC in the Western culture, but not in the Non-Western culture. There are no
cross-cultural differences on the association between ILOC and ELOC.
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Master Thesis - Lisette Feijen
Content
Preface ____________________________________________________________________________________________ 5
Acknowledgements ______________________________________________________________________________ 6
Summary __________________________________________________________________________________________ 7
1.
Introduction_________________________________________________________________________________ 15
1.1 Locus of Control ________________________________________________________________________________ 15
1.2 Short scales _____________________________________________________________________________________ 16
1.3 Response Categories ___________________________________________________________________________ 17
1.3.1 Cultural differences in extreme response style _________________________________________ 18
1.4 Culture and Locus of Control___________________________________________________________________ 19
1.5 Aim of research _________________________________________________________________________________ 20
1.6 Research questions and hypotheses ___________________________________________________________ 20
1.6.1 Theoretical model ______________________________________________________________________ 23
1.7 Relevance of research __________________________________________________________________________ 24
2.
Methods _____________________________________________________________________________________ 25
2.1 Development of 4-item LOC Scale _____________________________________________________________ 25
2.2 Sample __________________________________________________________________________________________ 26
2.3 Questionnaire ___________________________________________________________________________________ 27
2.4 Classification ____________________________________________________________________________________ 27
3.
Data Analysis________________________________________________________________________________ 29
3.1 Technical Design ________________________________________________________________________________ 29
3.2 Data analyses procedures ______________________________________________________________________ 30
3.2.1 Prior to data analyses___________________________________________________________________ 30
Correction for version ________________________________________________________________________ 30
Rescaling _____________________________________________________________________________________ 30
Factor analysis _______________________________________________________________________________ 31
Calculating scale scores for ILOC and ELOC __________________________________________________ 31
Extreme scores _______________________________________________________________________________ 31
Master Thesis - Lisette Feijen
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3.2.2 Analysis assumptions ___________________________________________________________________ 31
MANOVA - Normality ________________________________________________________________________ 31
MANOVA - Homogeneity ____________________________________________________________________ 32
Contingency tables - Chi-square test of homogeneity _______________________________________ 32
3.2.3 Statistics ________________________________________________________________________________ 32
Multivariate analysis of variance _____________________________________________________________ 32
Pearson Chi-square test ______________________________________________________________________ 32
Cochran’s chi-square test ____________________________________________________________________ 33
Correlations __________________________________________________________________________________ 33
4. Results _________________________________________________________________________________________ 34
4.1 Sample description _____________________________________________________________________________ 34
4.2 The effect on the relative mean of ILOC and ELOC ____________________________________________ 35
4.2.1. Item characteristics ____________________________________________________________________ 35
4.2.2 Principal Axis Factoring _________________________________________________________________ 35
4.2.3 Calculation of scale scores______________________________________________________________ 36
4.2.4 Multivariate Analysis of Variance _______________________________________________________ 36
4.3 The effect on the frequency of extreme scores for ILOC and ELOC ___________________________ 39
4.3.1 The number of response categories ____________________________________________________ 39
4.3.2 Culture _________________________________________________________________________________ 42
4.3.3 Interaction effect _______________________________________________________________________ 45
4.4 Association between Internal and External Locus of Control _________________________________ 47
4.4.1 Correlation coefficient __________________________________________________________________ 47
4.4.2 Cross-cultural differences on the association between Internal and External Locus of
Control _______________________________________________________________________________________ 47
5. Discussion _____________________________________________________________________________________ 48
5.1 Results __________________________________________________________________________________________ 48
5.1.1 Number of response categories ________________________________________________________ 48
5.1.2 Culture _________________________________________________________________________________ 49
5.1.3 Moderating effect of Culture ___________________________________________________________ 49
5.1.4. Association ILOC and ELOC ____________________________________________________________ 50
5.2 Strengths ________________________________________________________________________________________ 51
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Master Thesis - Lisette Feijen
5.3 Limitations ______________________________________________________________________________________ 51
5.4 Recommendations ______________________________________________________________________________ 52
6. References_____________________________________________________________________________________ 53
7. Appendices ____________________________________________________________________________________ 56
Appendix I – Questionnaire ________________________________________________________________________ 57
Appendix II – Syntax for SPSS ______________________________________________________________________ 60
Syntax 1 - Correction for version _____________________________________________________________ 60
Syntax 2 – Calculation of ILOC and ELOC ____________________________________________________ 60
Syntax 3 – Correction for scale width (via recoding) _________________________________________ 60
Syntax 4 – Calculation scale scores ILOC and ELOC __________________________________________ 61
Syntax 5 – Extreme scores____________________________________________________________________ 61
Syntax 6 – recode in no extreme and extreme score _________________________________________ 61
Appendix III – Output from SPSS __________________________________________________________________ 62
Principal Axis Factoring ______________________________________________________________________ 62
Correlations __________________________________________________________________________________ 65
Master Thesis - Lisette Feijen
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List of Tables
Table 2.1 Classification to cultural groups ______________________________________________________ 28
Table 2.2 Classification to dominant Cultures __________________________________________________ 28
Table 3.1 Group sizes for analysis ______________________________________________________________ 29
Table 4.1 Sample description per scale width __________________________________________________ 34
Table 4.2 Characteristics of items_______________________________________________________________ 35
Table 4.3 Characteristics of dimensions ________________________________________________________ 36
Table 4.4 Frequency of extreme score for each scale end for scale width ______________________ 39
Table 4.5 Contingency table Internal Locus of Control*Scale width ____________________________ 40
Table 4.6 Contingency table External Locus of Control*Scale width ____________________________ 41
Table 4.7 Frequency of extreme score for each scale end for culture ___________________________ 42
Table 4.8 Contingency table Internal Locus of Control*Culture_________________________________ 43
Table 4.9 Contingency table External Locus of Control*Culture ________________________________ 44
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Master Thesis - Lisette Feijen
List of Figures
Figure 1.1 Theoretical model with independent and dependent variables _____________________ 23
Figure 2.1 Locus of Control – Construct with two correlated dimensions ______________________ 26
Figure 3.1 Rescaling of 9-point scale ___________________________________________________________ 30
Figure 4.1 Mean of Internal Locus of Control for scale width ___________________________________ 36
Figure 4.2 Mean of External Locus of Control for scale width __________________________________ 36
Figure 4.3 Mean of Internal Locus of Control for culture _______________________________________ 37
Figure 4.4 Mean of External Locus of Control for culture _______________________________________ 37
Figure 4.5 Mean of Internal Locus of Control for version _______________________________________ 38
Figure 4.6 Mean of External Locus of Control for version_______________________________________ 38
Figure 4.7 Frequency of extreme scores for ILOC in short and wide scale ______________________ 40
Figure 4.8 Frequency of extreme scores for ELOC in short and wide scale _____________________ 41
Figure 4.9 Frequency of extreme scores for ILOC per culture___________________________________ 43
Figure 4.10 Frequency of extreme scores for ELOC per culture _________________________________ 44
Figure 4.11 Frequency of extreme scores for ILOC per scale width in Western culture _________ 45
Figure 4.12 Frequency of extreme scores for ILOC per scale width in Non-Western culture____ 45
Figure 4.13 Frequency of extreme scores for ELOC per scale width in Western culture ________ 46
Figure 4.14 Frequency of extreme scores for ELOC per scale width in Non-Western culture ___ 46
Master Thesis - Lisette Feijen
13
1. Introduction
Locus of Control (LOC) has been applied in different fields of research; psychology, behavioural
studies, health, and marketing. The past decades there has been a deep interest in the concept of
Locus of Control. It has been researched, adapted, improved and applied for specific contexts. The
concept is so broad that domain specific Locus of Control scales have been developed, such as the
Multidimensional Health Locus of Control Scale by Wallston, Wallston and DeVellis (1978), the
Multidimensional Traffic Locus of Control Scale (T-LOC) by Özkan and Lajunen (2005), Sales Locus
of Control Scale (SLCS) by Chung and Ding (2002), Weight Locus of Control Scale (WLOC) by Saltzer
(1982) and the Parental Locus of Control Scale (PLOC) by Campis, Lyman, and Prentice-Dunn (1986).
Although the scale itself is of particular interest, not only for the content but also for the length of
the scale, the response categories have received only minor alterations. Originally, it was a
dichotomous response scale (either yes or no) until 1972, after which Levenson used a 6-point
Likert-type scale, an ordinal scale, to measure LOC known as the ‘second-generation’. Since then,
researchers have used the Likert-type scale to measure LOC and use the Likert-type scale in the
development of their own scales. Researchers of the LOC construct use mostly 5 to 7 points
response categories out of convenience or tradition (Peter, 1979; Cox, 1980; Preston & Colman,
2000; Lozano, García-Cueto, & Muñiz, 2008). However, there is not sufficient research with respect
to the number of response categories in the LOC scale. This is important because the number of
response categories in a scale may have an influence on the reliability and the validity of the scale
(Lee & Paek, 2014). This gives reason to research the LOC construct further and the development
of LOC scales with regard to scale length and the number of response categories. This thesis
investigates what the influence of a larger number of response categories, 9-points, is on the data
structure of LOC. Data structure entails the relative mean, the frequency of extreme response, and
the covariance between LOC constructs.
1.1 Locus of Control
The construct of Locus of Control was first described by Rotter (1966). Locus of Control emerged
from his social learning theory. Locus of control is considered to be an aspect in the social learning
theory. In order to define Locus of Control, Rotter (1966) uses the following three concepts:
expectancy, behaviour potential, and reinforcement value. Locus of Control in the social learning
theory represents generalized expectancies and helps in the refinement of predicting
Master Thesis - Lisette Feijen
15
reinforcements to change behaviour. Change in behaviour or behaviour potential (BP) is a function
of the expectancies (E) and the reinforcement value (RV) in the formula: 𝐵𝑃 = 𝑓(𝐸 ∗ 𝑅𝑉). The
construct LOC is seen as generalized expectancies for control of reinforcement. Rotter (1966) set a
unidimensional scale with two ends. These ends are defined as respectively external and internal
LOC. External and internal Locus of Control have received many descriptions in literature (Rotter,
1966; Lefcourt, 1972; Smith, Dugan, & Trompenaars, 1997; Kovaleva, 2012), but all concentrate on
the same underlying thought. Rotter (1966) describes external LOC (ELOC) as beliefs that his/her
life is in the hands of his environment, fate, chance or others. Internal LOC (ILOC) is described as
beliefs that one is in charge of his/her own life.
The LOC construct was initially meant as a bipolar continuum (Rotter, 1966). However, many
researchers showed that LOC can be seen as a multidimensional construct (Lefcourt, 1972, 1976,
1992; Levenson, 1973; Wallston, Wallston, & DeVellis, 1978; Özkan & Lajunen, 2005). Although there
is no consensus about the unidimensionality or the multidimensionality in LOC, there is a distinction
in LOC between internal LOC and external LOC as two separate dimensions. Kovaleva (2012)
examined the factor structure of two LOC scales; German Social Economic Panel (GSOEP) and KMKB
by comparing two correlated factors with two independent factors with the help of Confirmatory
Factor Analysis (GSOEP) and Principal Component Analysis (KMKB). There is a good fit for the 2
correlated factors model in both scales while the 2 independent factors yield a poor fit. These factor
analyses also indicate a negative association between Internal LOC and External LOC (Kovaleva,
2012). For the purpose of this thesis LOC is assumed to have two correlated dimensions: internal
LOC and external LOC. Where internal LOC is defined as “belief that events in life are contingent on
one’s behaviour and these can be controlled by this”. And where external LOC is defined as
“personal belief that life events is contingent on external factors (others and bad luck) and they are
controlled by these factors”.
1.2 Short scales
There is a growing interest in shorter scales, which is also the case for LOC. Less items would be
easier to use, to interpret, and easier to integrate into existing questionnaires, because it takes a
small amount of space in a questionnaire and only a few items need to be analysed and interpreted.
Why use 29 items to measure LOC when you can also use 4 items? Short scales are seen as more
efficient and less time-consuming in practice. The test power is not decided by the number of items,
but relies more on the number of respondents (Scott et al., 2009; Kovaleva, 2012). The gain in power
from increasing the number of items occurs mostly when going from a two-item scale to a three
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Master Thesis - Lisette Feijen
item-scale (Scott et al., 2009). Scott el al. (2009) state that as a general rule of thumb to ensure
adequate statistical power (of the ordinal logistic regression) of >80% each group should exist of a
minimum of 200 respondents. For a two-item scale a minimum of 300 respondents was suggested.
However, scale length has an influence on specific psychometric properties, such as reliability
(Komorita & Graham, 1965; Lee & Paek, 2014). Lee and Paek (2014) state that shorter scales that
use less items (5 items vs. 20 items) seem to show a larger decline of the statistical properties
(reliability and validity), when the number of response categories is low. The number of response
categories is a moderator on the relationship between scale width and reliability. To prevent decline
in reliability when shortening the scale length, the number of response categories should be
broadened. There seems to be a combined effect between the number of items used (scale length)
and the number of response categories for these items. This combined effect is larger with respect
to correlation and reliability than for each effect separately, scale length or the number of response
categories. Therefore this combined effect as an unique contribution to changes in the
psychometric properties (Lee & Paek, 2014).
1.3 Response Categories
In general, there is no consensus regarding the optimal number of response categories, and much
is based on convenience or tradition (Cox, 1980; Fox & Jones, 1998; Lee & Paek, 2014). Most often,
between 4 and 6 response categories are chosen. However, item discrimination (success on an item
is also success on the test) is better in scales with a larger number of response categories than in
scales with a smaller number of response categories (Preston & Colman, 2000; Lee & Paek, 2014).
A greater number of response categories is associated with better psychometric properties such as
reliability and validity, when there are less items (Lee & Paek, 2014). Since reliability and validity are
associated with item variance, the item variance tend to be larger when there are more response
categories. In general the reliability increases as the number of response categories increases.
However, reliability decreases when item correlations decrease (Lozano et al., 2008). An optimal
number of response categories is often referred as an optimal range, although research (Givon &
Shapira, 1984; Lozano et al., 2008) has shown there was no difference between a 4-point scale and
a 7-point scale or between a 5-point scale and a 9-point scale with respect to test-retest reliability,
scale variance, Cronbach’s alpha and inter-item correlations (Lee & Paek, 2014). These nondifferences are based on scales with a large number of items, respectively 30 items (Lozano et al.,
2008) and 27 items (Givon & Shapira, 1984). This does not imply that there will be no differences
Master Thesis - Lisette Feijen
17
regarding test-retest reliability, scale variance, Cronbach’s alpha and inter-item correlations
between a 5-point scale and a 9-point scale for a short scale with a small number of items.
Research devoted to the effects of variations in rating scale formats, such as differences in
the number of response categories, in the field of psychology mostly use rating scales as a
measurement instrument (Preston & Colman, 2000). Measures with 9-point scale scores seem to
correlate better than 5-point scale scores and tend to suggest that measurement validity increases
with increasing number of response categories (Hancock & Klockars, 1991; Preston & Colman,
2000). Lozano et al. (2008) point out that the validity of the questionnaire is dependent on the
number of response categories. This is of importance because the number of response categories
potentially affects the measurement validity. Measurement validity is necessary in order to establish
that the instrument is measuring what it intends to measure and has the ability to distinguish
between groups (conform a given theory). A larger number of response categories should still have
measurement validity, otherwise the LOC construct is not measured as intended and cannot be
compared to other similar LOC measurement tools. It is important in this research that the LOC
construct has measurement validity when there is a higher number of response categories.
Response categories are either labelled at every category or only labelled at the end (no
verbal anchoring in-between). For example, ‘1=doesn’t apply at all, 2=applies a bit, 3=applies
somewhat, 4=applies mostly and 5=applies completely’ is labelling at every category and in no
verbal anchoring in-between it looks like ‘1=doesn’t apply at all and 5=applies completely’.
However, there is evidence that omission of a mid-point mainly effects the frequencies of the
neighbouring scale responses (Spagna, 1984 as cited in Dawes, 2002) and that mid-points do not
affect the mean of the response categories (Si & Cullen, 1998 as cited in Dawes, 2002).
1.3.1 Cultural differences in extreme response style
Extreme response style refers to a greater tendency of respondents to select the extremes of a
response scale (Johnson, 2005). Extreme response style is related to response categories. As Dawes
(2002) states “in general there is support for the view that more scale categories reduce the
incidence of extreme response, and may produce more dispersion in data”. However, Clarke III
(2001) found that increasing the number of scale categories beyond five categories had little effect
on extreme response. Johnson (2005) studied four relations between extreme response style and
the Hofstede’s cultural dimensions. One of the hypotheses he studied is: extreme response styles
may be more common among people from individualist countries and a moderate response style
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Master Thesis - Lisette Feijen
is more suited in collectivist countries. Johnson’s reason for this is that many studies have reported
evidence that acquiescence is more common in collectivist countries, since collectivistic people tend
to conform and agree with others. However, people from collectivist countries tend to have a
acquiescent response style (Smith, 2004; Johnson, 2005; Harzing, 2006). They act as ‘yea-sayers’ and
therefore do not score at the low end ‘doesn’t apply at all’ of either Internal Locus of Control or
External Locus of Control. Johnson (2005) also states that extreme response style may be more
common among people from individualist countries, because they are less concerned with the
consequences of expressing strong opinions (Harzing, 2006). Harzing (2006) mentions that
individualistic countries are expected a higher willingness to disagree, indicating an extreme
response style at the low end of the scale. The study of Johnson (2005) refutes the relation that
extreme response style is more common in individualist countries and results that individualism
was not associated with extreme response style. There are cross-cultural differences in extreme
response style and these are usually contrasted with a moderate response style. A moderate
response style is seen as the opposite of an extreme response style and used in cross-cultural
research for comparison (Hamamura, Heine, & Paulhus, 2008). Smith (2004) states that response
style differences might come from psychological constructs, because cultural trends in response
style might be due to response habit only. Having an extreme response style (mostly individualistic
countries) or having a moderate response style (mostly collectivistic countries) could be related to
having either more ILOC or ELOC.
1.4 Culture and Locus of Control
Individualism and collectivism exists in all cultures and countries, but one tends to predominate.
Individualism predominates in Europe, USA, Canada, Australia and New Zealand. Individualist
countries are mainly Anglo-European countries, but also other western countries are considered to
be individualistic (Frese, Kring, Soose, & Zempel, 1996; Spector et al., 2002). People in individualistic
cultures, and thus countries, value independence and achievement through their own actions.
Countries with a predominant collectivistic culture are mainly found in Africa, Latin America and
Asia (Gudykunst, 1998). People in collectivist countries value autonomy less and perceive less
autonomy than people in individualist countries (Spector et al., 2001). This means that people in
collectivist countries feel less moral responsibility and accountability for one’s actions and find this
less important. Thus, collectivist countries are less inclined to have high Internal Locus of Control.
Besides this, collectivistic Asians are more external in their general Locus of Control than
individualistic Americans and people from other western countries (Hui, 1982; Spector et al., 2001),
Master Thesis - Lisette Feijen
19
since they feel that others have control over their actions which is related to External Locus of
Control. Eastern European countries, former Soviet Republic, are also collectivistic (Spector et al.,
2001) as well as other Asian countries and Latin America (Spector et al., 2002). So, Internal Locus of
Control is mostly present in individualist countries and less present in collectivist countries.
1.5 Aim of research
Locus of Control is a construct that is present in each culture, but can also be sensitive to values of
autonomy and cultural norms and values. Therefore, it is interesting to investigate LOC across
cultures. A heterogeneous sample in terms of culture is necessary to investigate these cross-cultural
differences or similarities. Next to cross-cultural aspects of LOC, there is a growing global interest
in short scales and the practical use of these. Shorter scales tend to, according to Lee and Paek
(2014), need larger number of response categories in order to stay reliable. So, how to decide on
the number of response categories to use? There is no clear formula or standard. Most research
about Locus of Control use five or six response categories. The scale length remains the same in
this research, the focus is on the number of response categories. In this research a comparison is
made between five response categories and nine response categories. The aim is to investigate the
effect of the number of response categories on the data structure of the LOC construct and to
perform a cross-cultural analysis in order to gain insight into culture as a moderator.
1.6 Research questions and hypotheses
There are four research questions. These research questions are supported by 14 hypotheses,
alternative hypotheses are given (for one-sided hypotheses the null hypothesis is given as well).
The dependent variables are Internal Locus of Control (ILOC) and External Locus of Control (ELOC).
This thesis investigates the relative mean and extreme response (data structure) as hypothesized.
Besides this, between group comparisons are made based on culture. Research question 1 and 2
are main effects of the independent variables on the dependent variables. Culture is perceived as a
moderator in research question 3. Also the correlation between the two dependent variables ILOC
and ELOC is investigated, as well as the cross-cultural differences in this association, research
question 4. This is further explained in chapter 2, Methods.
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Master Thesis - Lisette Feijen
Research question 1
What is the effect of the number of response categories on the data structure of the LOC construct?
Hypothesis 1: The relative mean of the short scale for ILOC differs from the relative mean of the
wide scale for ILOC.
Hypothesis 2: The relative mean of the short scale for ELOC differs from the relative mean of the
wide scale for ELOC.
Hypothesis 3: The frequency of extreme scores of ILOC on the short scale differs from the
frequency of extreme scores of ILOC on the wide scale.
Hypothesis 4: The frequency of extreme scores of ELOC on the short scale differs from the
frequency of extreme scores of ELOC on the wide scale.
Research question 2
What is the effect of culture on the data structure of the LOC construct?
Hypothesis 5: There are cross-cultural differences in the relative mean of ILOC.
Hypothesis 6: There are cross-cultural differences in the frequency of extreme scores
of ILOC.
Hypothesis 7: There are cross-cultural differences in the relative mean of ELOC.
Hypothesis 8: There are cross-cultural differences in the frequency of extreme scores
of ELOC.
Master Thesis - Lisette Feijen
21
Research question 3
Are there cross-cultural differences in the effect of the number of response categories on the data
structure of the LOC construct?
Hypothesis 9: There are cross-cultural differences regarding the effect of the number of
response categories on the relative mean of ILOC.
Hypothesis 10: There are cross-cultural differences regarding the effect of the number of
response categories on the frequency of extreme scores of ILOC.
Hypothesis 11: There are cross-cultural differences regarding the effect of the number of
response categories on the relative mean of ELOC.
Hypothesis 12: There are cross-cultural differences regarding the effect of the number of
response categories on the frequency of extreme scores of ELOC.
Research question 4
Are there cross-cultural differences in the association between ILOC and ELOC?
Hypothesis 13: There is a negative association between ILOC and ELOC.
H0: there is no association between ILOC and ELOC
Hypothesis 14: There are cross-cultural differences regarding the association between
ILOC and ELOC.
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Master Thesis - Lisette Feijen
1.6.1 Theoretical model
In Figure 1.1 a schematic view of the theoretical model with the independent and dependent variables is shown, including the effects studied.
Figure 1.1 Theoretical model with independent variables ‘number of response categories’ and ‘culture’ and dependent variables ‘Internal Locus of Control’ and ‘External Locus of
Control’
Main effect: Black arrow | RQ 1+ 2
Association/correlation: Green arrow | RQ 4
Interaction Effect: Blue arrow | RQ 3
Effect: Purple arrow | RQ 4
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Master Thesis - Lisette Feijen
1.7 Relevance of research
This research further elaborates on scale effects within a cross-cultural context. The number of
response categories has been researched by many, however not in relation to Locus of Control.
Also the use of a short scale with just four items in combination with a variety in number of response
categories has not yet been subject of investigation. Besides that, a short four-item scale with an
effect of the number of response categories may influence other researchers to look further in
developing or adjusting scales to be shorter.
From a societal point of view, this research gives insight in differences and similarities between
cultures. Any insights on cross-cultural issues give researchers and implementers knowledge that
could be used in a practical matter in the everyday field, but also knowledge to further investigate
cultural issues.
In relation to health, Locus of Control is a well-established concept at a macro level. A review by
Wallston, Wallston, and DeVellis (1978) looked into Locus of Control in different health behaviours.
These health behaviours include smoking, birth control and weight loss as well as sick-role
behaviour. Locus of Control is important in predicting health behaviour and sick roles. Specific
health behaviours are: seeking information, taking medication, making and keeping appointments
with the physician, maintaining a diet and giving up smoking. Both Internals and Externals have a
belief to deal with these behaviours, the health professionals can adapt current affairs to make
healthy behaviour easier for all. In other words, tailoring health programs to the individuals’ Locus
of Control. Suggested in Wallston et al. (1978) is that internally orientated health programs can
provide more choice of treatment, more involvement of the patient in making choices and
emphasize on individual responsibility. Whereas externally oriented health programs rely more on
social support systems and the importance of compliance with the health professional (Wallston et
al., 1978). A short scale for LOC could be more easily implemented in current activities by health
professionals. Also cross-cultural differences would help guide the health professional to give
tailored advice.
24
Master Thesis - Lisette Feijen
2. Methods
In this section the development of the 4-item LOC scale, a fundamental part in this research, is
described. After this, the sample, questionnaire, group classification and data analyses procedures
of this research are described.
2.1 Development of 4 -item LOC Scale
This research used the 4-item LOC scale as developed by GESIS (Kovaleva, 2012). This scale was
constructed after comparing four existing LOC scales (ROT-IE, IPC, GSOEP, KMKB). ROT-IE is the 29
item unidimensional scale by Rotter (1966) , IPC is the 24 item multidimensional scale developed
by Levenson (1972), GSOEP (German Social Economic Panel) is a German scale that used 8 items to
measure LOC with two (internal and external) dimensions (Nolte, Weischer, Wilkesmann, Maetzel,
& Tegethoff, 1997) and KMKB is also a German scale which measures LOC, but used only 6 items.
The KMKB used two separate subscales, one for ILOC and one for ELOC, each consisted of three
items (Jakoby & Jacob, 1999). These four scales (ROT-IE, IPC, GSOEP and KMKB) were the basis of
the 4-item LOC scale.
The process of developing this 4-item scale, executed by Kovaleva (2012) consisted of four steps.
The first step was comparing the LOC scales selected and identifying the crucial aspects of LOC.
The four crucial aspects of the concept LOC were 1) the expectancy of personal belief to have
control over life events (ILOC), 2) the expectancy of a contingency between one’s efforts and the
results achieved (ILOC), 3) the expectancy of power of other people (ELOC) and 4) the expectancy
of chance and fate (ELOC). The second step was creating an item pool consisting of 20 items, 10 for
ILOC and 10 for ELOC. This was done to be able to start the reduction process. The reduction
process took place based on criteria as: avoiding words denoting quality or quantity, fluency, and
short sentences were preferred. The 20-item pool was reduced to 10 items, 5 for ILOC and 5 for
ELOC. Next to testing the content of items via interviews (in the third step) with regard to possible
response bias in relation to level of education, there remained a selection of items based on
psychometric properties (reliability and inter-item correlations). Via Exploratory Factor Analysis
(EFA) the item pool was reduced to four items only (the fourth step), taking into account the four
crucial aspects of LOC and the factor loadings (Kovaleva, 2012).
Master Thesis - Lisette Feijen
25
Originally this short LOC scale and the items were in German, however GESIS made an English
translation of the scale (Kovaleva, 2012). The four items were formulated as follows: 1) “I’m my own
boss”, 2) “If I work hard, I will succeed”, 3) “Whether at work or in my private life: what I do is mainly
determined by others” and 4) “Fate often gets in the way of my plans”. The Research Methodology
chair group of the Wageningen University adapted fate into bad luck as perceptions of fate differed
between cultures. This English scale is the base of the LOC construct in this thesis. The 4-item scale
for LOC is shown in Figure 2.1.
Internal
Locus of
Control
External
Locus of
Control
(ILOC)
(ELOC)
BOSS
SUCCEED
OTHERS
BAD LUCK
Figure 2.1 Locus of Control – Construct with two correlated dimensions and two items per dimension
2.2 Sample
There were two independent samples each receiving a different number of response categories.
One sample (in the year 2013) received a 5-point Likert scale, the short scale, and the other sample
(in the year 2014) received a 9-point Likert scale, the wide scale. For the short scale and the wide
scale the sample sizes were respectively: n=278 and n=222. Respondents were students in either a
Master in Environmental Studies or a Master in Social Studies. The students signed in on either of
two similar courses, YRM-20306 and YRM-20806, at the University of Wageningen. The courses
were similar with respect to learning objectives, prerequisite demands and format (lectures,
workshops and group work).
26
Master Thesis - Lisette Feijen
2.3 Questionnaire
The questionnaires had either a short scale or a wide scale. The short scale functioned as reference
year. There were also two versions for each scale. The manipulation of ordering in the two versions
originated from a preceding research and was thus an independent variable in this study.
The questionnaire (appendix I) was distributed during a course at the University of Wageningen.
The teacher was asked to hand-out the versions of the questionnaire randomly among the students.
The number of questionnaires and equal proportion of versions was taken into account beforehand.
Participation was on voluntary basis and anonymous. The questionnaire was in English, a non-native
language for most of the respondents (n=489; 97,8%). Respondents were asked to fill in
characteristics, such as: age, gender, country of origin and first language. Other questions in the
questionnaire entailed satisfaction with working in groups at the university, number of time spent
on working for the course, English proficiency skills (read, write, hear, speak) and the 4-item LOC
construct.
2.4 Classification
The classification to create cultural groups for comparison was based on Tobi and Kampen (2013),
which is a precursor of this research and handles similar data. The classification was adapted
according to the actual data acquired. Adaptions made included combining regions such as
Germanic Africa and other Africa into Africa, because there were low n-values (German Africa: 21;
Other Africa: 10) and including more countries (added countries) based on raw data (see Table 2.1).
Table 2.1 shows eight cultural groups from all over the world. These cultural groups (and its
countries) were identified as individualistic or collectivistic. The individualistic cultural groups were
defined as western societies, whereas the collectivistic cultural groups were non-western societies.
This means that there are two dominant cultures, Western versus Non-Western which consist of
several cultural groups, Table 2.2 gives an overview of this. The reason to compress the cultural
groups to two dominant cultures was to make cultural groups comparable with one another, since
group size of cultural groups differed very much. Thus creating similar group sizes, which was
desirable for the multivariate analysis.
Master Thesis - Lisette Feijen
27
Table 2.1 Classification to cultural groups
Added countriesb
Cultural group
Countries
Latin America
Surinam, Colombia, Honduras, Ecuador,
Cuba, Panama
c
Mexico, Bolivia, Peru, Chile, Costa Rica ,
Brazil
Africa
Eritrea, Ghana, Kenya, Tanzania, South
c
Morocco
c
Africa , Zimbabwe, Cameroon , Nigeria,
Zambia,
Uganda,
Ethiopia,
c
Mozambique , Senegal
Rwanda,
c
Dutch
The Netherlands
Germanic Europe
UK, Sweden, Norwayc, Belgium, Germany
Latin Europe
c
Romania, Moldavia Republic ,
Austria, Switzerland
France,
Spain, Italy, Portugal
Other Europe
Hungaryc, Finland, Lithuania, Albaniac,
c
c
Cyprus,
c
Tadzjikistana,
Armenia , Greece, Macedonia , Turkey ,
Czech
Republic,
c
Slovakia,
Ukraine ,
c
Poland , Serbia , Croatia, Bulgaria
China
China
Other Asia
Malaysiac, Sri Lanka, Indonesia, Nepal,
c
c
Bhutan , India, Mongolia , Bangladesh,
c
c
Russia, Uzbekistan, Yugoslavia,
c
c
Vietnam , Cambodia , Laos , Thailand,
Kazakstana
,
Kyrgyzstana
Iran,
,
Afghanistan,
Brunei,
Taiwan, Korea, Iraq, Pakistan,
Japan
Philippines
a
based on main language and only recently independent from Soviet Republic. Officially part of central-Asia.
Not included: Canada
c
No respondents in this study
b
Table 2.2 Classification to dominant Cultures
Dominant Culture
Cultural group
Western
28
Non-Western
Latin America
Dutch
Africa
Germanic Europe
Other Europe
Latin Europe
China
Other Asia
Master Thesis - Lisette Feijen
3. Data Analysis
In this chapter the technical design of this research is elaborated on, as well as the data analyses
procedures.
3.1 Technical Design
A quasi-experimental design with two dependent variables and three independent variables, a 2 x
2 x 2 (Scale width [short scale, wide scale] x Culture [Western, Non-Western] x Version [Order 1 vs.
Order 2]) design (see Table 3.1). The dependent variables are Internal Locus of Control (ILOC) and
External Locus of Control (ELOC).
Table 3.1 Group sizes for analysis
Number of response categories
Short scale
Wide scale
Total
Order 1
78
61
n=139
Order 2
46
65
n=111
Non-
Order 1
76
46
n=122
Western
Order 2
67
45
n=112
n=267
n=217
N=484
Culture
Western
Total
Note: group sizes in conditions are based on the combined use of ILOC and ELOC in a MANOVA
The interest in this study lay on the relative mean and the frequency of extreme scores for these
two dependent variables. There were three independent variables ‘scale width’, ‘culture’ and
‘version’. The independent variable ‘scale width’ refers to the number of response categories used,
and is of the most interesting in this specific research. The independent variable ‘culture’ (originated
from country of origin) is first classified to eight cultural groups and derived from this classification
two dominant cultures emerged: Western versus Non-Western. The independent variable ‘version’
was a manipulation (ordering) in the questionnaire that was already present and therefore was
taken into account.
Master Thesis - Lisette Feijen
29
3.2 Data analyses procedures
IBM SPSS Statistics 22.0 © Copyright IBM Corporation and other(s) 1989-2013 was used for data
entry, data management and data analysis.
3.2.1 Prior to data analyses
There were five steps prior to the data analyses: 1) correction for question order, 2) rescaling, 3)
factor analysis, 4) calculating scale scores for ILOC and ELOC and 5) extreme scores. The steps were
crucial for analysing the data properly.
Correction for question order
The data entry needed to be corrected for version since question order differed (appendix II; syntax
1). From the corrected item scores, scale scores for ILOC and ELOC are computed (appendix II;
syntax 2).
Rescaling
A rescaling took place to correct for scale width in order to make the data from both scale widths
comparable. The 5-point scale was used as reference and the 9-point scale was rescaled to a 5point scale. So, the width of both scales became the same. The number of response categories in
the rescaled scale were the same as in the original and there was an assumption of equal intervals
between the response categories. To support this rescaling the following formula was applied:
new rating = SUM(old plus preceding ratings)⁄#involved response categories.
All item scores were recoded (see appendix II; syntax 3). This resulted in a recode of the 9-point
scale illustrated in Figure 3.1.
Figure 3.1 Rescaling of 9-point scale, scale ends correspond with a 5-point scale, number of categories equal
to nine and equal distances between categories
Rescaling was also important with regard to the Principal Axis Factoring (PAF), since a PAF on the
full dataset gives the required factor structure (despite any manipulation of scale width). PAF on
raw data would have resulted in an unjustified factor structure because the scale widths are not
comparable in the raw data and a one-factor structure would emerge.
30
Master Thesis - Lisette Feijen
Factor analysis
To determine the factor structure of Locus of Control in this sample a Principal Axis Factoring was
performed. The input for this factor analyses were the rescaled item scores. The number of factors
extracted was based on eigenvalues > 1 to give the PAF the freedom to extract the actual number
of factors. An oblique rotation was added to allow for correlating factors, since this is expected from
research (Kovaleva, 2012). A pattern matrix provided the factor structure (see appendix III). This
procedure was performed for the full dataset and for Western and Non-Western culture separately
(appendix III).
Calculating scale scores for ILOC and ELOC
In order to compute scale scores for ILOC and ELOC the factor structure was important. Based on
the factor structure ELOC was computed by adding the item scores and calculating the mean. This
process was also done for ILOC (see appendix II; syntax 4). For respondents that have one or more
missing item scores a dimension score cannot be computed, since each dimension needs two item
scores in order for it to be calculated.
Extreme scores
Frequency of extreme scores is operationalized as having an extreme score (1 or 5) on either or
both items. Respondents had no extreme score or an extreme score on either or both of the
dependent variables (DVs). All extreme scores were recoded into a 1 (extreme score) for each item,
the non-extreme scores (1.5 – 4.5) were recoded into a 0 (no extreme score). These scores, both
extreme and non-extreme, on the items are summed for each DV leading to values ranging from 0
to 2 (appendix II; syntax 5). A zero meant that there was no extreme score at all, a one or two
indicated that at least one of the two items for that DV had an extreme score. An extreme score
was identified when at least one of the two items for that DV had an extreme score. Therefore the
DV scores were re-coded in only a 0 (no extreme score) or 1 (at least on extreme score) (appendix
II; syntax 6).
3.2.2 Analysis assumptions
MANOVA - Normality
The normality check via visual inspection of univariate normality (Q-Q plots, histograms and
characteristics of the dependent variables) and bivariate normality (bivariate scatterplots) revealed
a sufficient normal distribution. The Q-Q plot indicated that the observations in each cell followed
the normal distribution, with a slight skewness. The histograms confirmed these slightly skewed
distributions. The mode, mean and median of both dimensions were not in the centre of the range
Master Thesis - Lisette Feijen
31
(3.0), but the actual range did not have the full range (5.0) either. So, the distribution was a bit
shifted from the centre, but this is not a problem for normality. The bivariate scatterplots showed
an ellipse form when looking at 60% around the centre (largest cluster of observations). Many
observations had the same values, this fact had to be taken into account in the interpretation of
the scatterplots.
MANOVA - Homogeneity
The tests for equality of variances showed Box’s M (p=.000) and Levene’s test for ILOC (F 7,475=3.45,
p=.001) and for ELOC (F7,475=3.18, p=.003). The null hypotheses of equality of variances was
rejected, there was a difference between the variances of the groups in the sample. However, the
group sizes of each cell in the 2 x 2 x 2 (Scale width [short scale vs. wide scale] x Culture [Western
vs. Non-Western] x Version [Order 1 vs. Order 2]) analysis of variance (ANOVA) were similar enough
by a rule used in practice: smallest group*1.5 is maximum size largest cell. Therefore, the test for
equality of variances can be considered as sufficient. So, the assumption of homogeneity was
sufficient.
Contingency tables - Chi-square test of homogeneity
The analysis assumption was that the expected count must be at least 1 and no more than 20% of
the expected counts can be less than 5. In the designs 0 cells (0.0%) had an expected count less
than 5.
3.2.3 Statistics
In the data analysis five procedures were used to test the hypotheses posed.
Multivariate analysis of variance
A multivariate analysis of variance (MANOVA) of the 2 x 2 x 2 design was performed to test the
main effects of the number of response categories (hypotheses 1 and 2), the main effect of culture
(hypotheses 5 and 7) and the effect of culture on the effect of the number of response categories
(hypotheses 9 and 11). Other interaction effects were also tested, because they were part of the
technical design.
Pearson Chi-square test
Based on the theoretical model there were two contingency tables tested for each DV. The
contingency tables for scale width had a 2 x 2 (Extreme scores [no extreme score vs. extreme score]
x Scale width [short scale vs. wide scale]) design (hypotheses 3 and 4). The contingency tables for
culture has a 2 x 2 (Extreme scores [no extreme score vs. extreme score] x Culture [Western vs. Non32
Master Thesis - Lisette Feijen
Western]) design (hypotheses 6 and 8). On all contingency tables a χ2 test of homogeneity was
performed. A Pearson Chi-square was calculated to test if the column distributions (frequencies
extreme scores and no extreme scores) are the same. Also the odds ratio was calculated indicating
the odds that there is an extreme score in the short scale compared to the odds of an extreme score
is the wide scale. This odds ratio is a measure for effect size or strength.
Cochran’s chi-square test
A test of conditional independence (Ott & Longnecker, 2010) was performed by calculating
Cochran’s chi-square to test cross-cultural differences regarding the effect of the number of
response categories on the frequency of extreme scores (hypotheses 10 and 12). This test statistic
tests a set of q 2x2 contingency tables. In this study q represented culture, there were 2 groups, so
q=2.
Correlations
A Pearson correlation coefficient was calculated to test a negative association between ILOC and
ELOC (hypothesis 13). To test cross-cultural differences regarding the association between ILOC
and ELOC (hypothesis 14) a test of the difference between two independent correlation coefficients
was done by following the procedure of Preacher (2002). Each correlation coefficient was converted
to a z-score by Fisher’s r-to-z transformation and these z-scores together with the sample sizes are
compared using formula 2.8.5 provided by Cohen & Cohen (1983) (cited by Preacher, 2002).
Master Thesis - Lisette Feijen
33
4. Results
In the first section, the results of this study regarding the relative mean of ILOC and ELOC are
presented. First, basic characteristic of the items are described. Second, a Principal Axis Factoring
(PAF) on the items gives the factor structure for further analyses. Based on this, Internal Locus of
Control and External Locus of Control scale scores are calculated. Lastly, a multivariate analysis of
variance (MANOVA) on the 2 x 2 x 2 (Scale width [short scale vs. wide scale] x Culture [Western vs.
Non-Western] x Version [Order 1 vs. Order 2]) is performed to test hypotheses 1, 2, 5, 7, 9 and 11.
The second section presents the results regarding the frequency of extreme response for ILOC and
ELOC, testing hypotheses 3, 4, 6, 8, 10, 12. Lastly the association between ILOC and ELOC,
hypotheses 13 and 14, is presented.
4.1 Sample description
The sample sizes for the short and wide scale were respectively: n=278 and n=222. In total there
were 500 respondents, people from the Western culture and Non-Western culture were included.
This meant that three respondents were excluded, because of their country of origin (Canada and
two error codes1). There were six missing values for culture. The total number of respondents
N=491. A description of the sample per scale width is shown in Table 4.1. The age distribution of
the respondents of the short scale ranged from 20 to 43 years. Most respondents are 23 years old
(n=68; 24,5%), or 22 years old (n=38; 13,7%). The age distribution ranged from 19 to 36 years for
the wide scale. Most respondents were 22 years old (n=57; 25,7%), or 23 years old (n=45; 20,3%).
Table 4.1 Sample description per scale width (N=491)
N
%
Short scale
Wide scale
Total
Short scale
Wide scale
Sample size
270
221
491
55.0
45.0
Course
YRM-20806
YRM-20306
123
116
239
45.6
52.5
147
105
252
54.4
47.5
Version
Order 1
Order 2
155
110
265
57.4
49.8
115
111
226
42.6
50.2
Gender
Male
Female
124
99
223
45.9
44.8
146
122
268
54.1
55.2
1
34
Error code is a numerical code that is not identified in the codebook and the original data (questionnaires) could not be consulted
since these are missing from the archive.
Master Thesis - Lisette Feijen
4.2 The effect on the relative mean of ILOC and ELOC
4.2.1. Item characteristics
The four rescaled items had n=486 (Boss), n=488 (Succeed, Others, Bad Luck). There were missing
values for all items; Boss had five missing values; Succeed, Others, Bad Luck had three missing
values each. Characteristics of these items were the mean, median, mode, range and standard
deviation (see Table 4.2). The means, medians and modes are close to each other and the range is
the same for each item. The most deviant item is Succeed, because there is some diversity between
the mean, median and mode.
Table 4.2 Characteristics of items
Std.
Mean
Median
Mode
Boss
3.703
4.0
4.0
.9678
4.0
Succeed
4.300
4.5
5.0
.7282
4.0
Others
2.096
2.0
2.0
.8169
4.0
Bad Luck
2.144
2.0
2.0
.8909
4.0
Deviation
Range
4.2.2 Principal Axis Factoring
In the Principal Axis Factoring (PAF) the rescaled items were used as input, total N=491. In SPSS a
PAF was run and the number of factors was based on eigenvalues > 1. This resulted in a total
variance explained of 33.5% and two factors were extracted. The pattern matrix (appendix III)
showed factor 1 ‘External Locus of Control’ had two items; Others (λ=.442) and Bad Luck (λ=.728),
and factor 2 ‘Internal Locus of Control had also two items; Boss (λ=.647) and Succeed (λ=.422). The
factor correlation matrix (appendix III) indicated that there was indeed a negative correlation, r=.172, between the two factors; ILOC and ELOC. In the Western culture two factors were extracted
(based on eigenvalues > 1) with a 30.7% Total variance explained. The pattern matrix (appendix III)
of the Western culture showed factor 1 ‘Internal Locus of Control’ had two items; Boss (λ=.584) and
Succeed (λ=.568) and factor 2 ‘External Locus of Control’ had also two items; Others (λ=.610) and
Bad Luck (λ=.421). The factor correlation matrix (appendix III) of the Western culture indicated that
there was a negative correlation, r=-.281, between the two factors. In the Non-Western culture
there are also two factors extracted based on eigenvalues >1. This resulted in a total variance
explained of 40.6%. Factor 1 ‘External Locus of Control’ had two items; Others (λ=.432) and Bad
Luck (λ=.883), and factor 2 ‘Internal Locus of Control had also two items; Boss (λ=.672) and Succeed
(λ=.414), shown by the pattern matrix (appendix III). The factor correlation matrix (appendix III) of
Master Thesis - Lisette Feijen
35
the Non-Western culture indicated that there was a negative correlation, r=-.105, between the two
factors.
4.2.3 Calculation of scale scores
The calculation of scale scores for ILOC and ELOC resulted in a n=485 (for ILOC) and a n=487 (for
ELOC). These scale scores for ILOC and ELOC were used for further analyses: Multivariate Analysis
of Variance and correlation coefficients. Some characteristics of the scale scores are shown in Table
4.3. The mean, median and mode are close to each other for each DV. There is a shorter range for
ELOC than for ILOC.
Table 4.3 Characteristics of dimensions
Internal Locus of
Control
External Locus of
Control
Mean
Median
Mode
Std.
Deviation
Range
3.998
4.0
4.0
.6807
4.0
2.118
2.0
2.0
.6971
3.5
4.2.4 Multivariate Analysis of Variance
The assumptions of normality and homogeneity were checked before analysis, see chapter 3.
The effect of the number of response categories
In the MANOVA there were two dependent variables: ILOC and ELOC and three independent
variables: scale width, culture and version. The multivariate test showed a main effect of the number
of response categories, indicated by scale width F1,475=15.7, p=.000, ηp2=.062 (medium effect size).
Figure 4.1 Mean of Internal Locus of Control for scale width
36
Figure 4.2 Mean of External Locus of Control for scale width
Master Thesis - Lisette Feijen
The univariate tests showed this main effect for the DV ELOC (F 1,475=25.2, p=.000) and for the DV
ILOC (F1,475=4.1, p=.043). These effects had small effect sizes ILOC: ηp2= .009 and ELOC: ηp2=.050
(almost medium effect size). Hypotheses 1 and 2 were accepted. The mean (SD) of ILOC for the
wide scale was higher M=4.1 (.587) than the short scale M=3.9 (.743), see Figure 4.1. In Figure 4.2
the mean (SD) of ELOC for the wide scale is higher M=2.3 (.682) than the short scale M=1.9 (.665).
The manipulation had the same effect on the mean score differences for ILOC and ELOC. In other
words, the mean of the wide scale was higher than the mean of the short scale despite ILOC and
ELOC.
The effect of culture
There is no significant effect of culture on the relative mean of Locus of Control (p=.395). This effect
is also not present at univariate level, ELOC (p=.461) and ILOC (p=.232). Our hypotheses 5 and 7
were rejected. Figure 4.3 and Figure 4.4 show the mean of resp. ILOC and ELOC for culture and
shows that the means are similar.
Figure 4.3 Mean of Internal Locus of Control for Culture
Master Thesis - Lisette Feijen
Figure 4.4 Mean of External Locus of Control for Culture
37
The effect of version
There is no significant effect of version on the relative mean of Locus of Control (p=.247). This effect
is also not present at univariate level for ELOC (p=.327) and for ILOC (p=.208). The means for ILOC
and ELOC are shown in Figure 4.5 and Figure 4.6. The mean are similar, there is an indication that
order 2 increases the mean for both ILOC and ELOC.
Figure 4.5 Mean of Internal Locus of Control for Version
Figure 4.6 Mean of External Locus of Control for Version
The interaction effects
There were four interaction effects tested between the IV’s; scale width, culture and version. There
were three two-way interactions and one three-way interaction. No significant interaction effect
was present, not on multivariate nor on univariate level. The interaction scale width*culture
(p=.758), the interaction scale width*version (p=.477), the interaction culture*version (p=.471) and
the interaction scale width*culture*version (p=.643). Hypotheses 9 and 11 were rejected. Western
and Non-Western cultures are equally sensitive to the manipulation of scale width and version.
Version had no interaction effect with scale width and two versions of the questionnaire have no
significant effect on the effect of the number of response categories. Scale width did not interact
in combination with the other two IV’s.
38
Master Thesis - Lisette Feijen
4.3 The effect on the frequency of extreme scores for ILOC and ELOC
There was missing data on extreme scores for both ILOC and ELOC, both had two missing values
which resulted in a N=489.
4.3.1 The number of response categories
An overview of the extreme scores on both ends for each scale width is given in Table 4.4. This
shows that extreme score on ILOC are mainly at the high end (‘applies completely’) while the
extreme scores on ELOC are mainly at the low end (‘doesn’t apply at all’). There is also a difference
between the short and the wide scale.
Table 4.4 Frequency of extreme scores for each scale end (1 and 5) for scale width
Width
Short
Wide
1
5
1
5
Boss
14
46
2
23
Succeed
2
119
.
54
Others
84
1
15
.
Bad Luck
82
2
18
3
Internal Locus of Control
The percentage of extreme scores in the short scale is 68.4% and in the wide scale is 31.6%, n=206
(see table 4.5 and figure 4.7). To test if there was a difference in frequency in extreme scores for
scale width (hypothesis 3) a Pearson chi-square test was performed. The test statistic χ2=25.9
(α=.05), df=1, p=.000. The column distributions were not the same. Hypothesis 3 was accepted.
There was a difference between the scale widths. The odds of an extreme score in the wide scale
was 0.381 times the odds of an extreme score in the short scale with a 95% CI [.261 , .554]. It was
2.6 times, 95% CI [1.8 , 3.8], more likely that a person scores an extreme value in the short scale
than in the wide scale.
Master Thesis - Lisette Feijen
39
Table 4.5 Contingency table Internal Locus of Control*Scale width
Scale width
Internal Locus of
no extreme value
of Control
extreme value
scale
scale
Total
128
155
283
45,2%
54,8%
100,0%
141
65
206
68,4%
31,6%
100,0%
269
220
489
55,0%
45,0%
100,0%
Count
% within Internal Locus
of Control
Total
Wide
Count
% within Internal Locus
Control
Short
Count
% within Internal Locus
of Control
n=65
n=141
Figure 4.7 Frequency of extreme scores for ILOC in
short and wide scale
40
Master Thesis - Lisette Feijen
External Locus of Control
The percentages of extreme scores are resp. 81% (short scale) and 19% (wide scale), n=158 (see
Table 4.6 and Figure 4.8). To test if there is a difference in frequency in extreme scores for scale
width (hypothesis 4) a Pearson chi-square test was performed. The test statistic χ2=64.7 (α=.05),
df=1, p=.000. The column distributions are not the same. Hypothesis 4 is accepted. There is a
difference between the scale widths. The odds of an extreme score in the wide scale was 0.172 times
the odds of an extreme score in the short scale with a 95% CI [.109 , .270]. It was 5.8 times, 95% CI
[3.7 , 9.2], more likely that a person scores an extreme value in the short scale than in the wide scale.
Table 4.6 Contingency table External Locus of Control*Scale width
Scale width
Wide
Short scale
External Locus of
no extreme value
Count
% within External
Control
Locus of Control
extreme value
Count
Locus of Control
Count
Total
% within External
Locus of Control
Total
140
191
331
42,3%
57,7%
100,0%
30
158
81,0%
19,0%
100,0%
268
221
489
54,8%
45,2%
100,0%
128
% within External
scale
n=30
n=128
Figure 4.8 Frequency of extreme scores for ELOC in
short and wide scale
Master Thesis - Lisette Feijen
41
4.3.2 Culture
An overview of the extreme scores on both ends for each dominant culture is given in table 4.7.
This shows that extreme score on ILOC are mainly at the high end (‘applies completely’) while the
extreme scores on ELOC are mainly at the low end (‘doesn’t apply at all’). There is not much
difference between Western and Non-Western, except for the item Succeed (and thus DV ILOC).
Table 4.7 Frequency of extreme scores for each scale end (1 and 5) for culture
Culture
Western
Non-Western
1
5
1
5
Boss
4
34
12
35
Succeed
1
65
1
108
Others
43
.
56
1
Bad Luck
48
1
52
4
Internal Locus of Control
To test if there was a cross-cultural difference in the frequency of extreme scores (hypothesis 6) a
Pearson chi-square was calculated to test if the column distributions (frequencies of extreme scores
and no extreme scores) are the same. The percentage of extreme scores in the Western Society is
38.8% and in the Non-Western Society is 61.2%, n=206 (see Table 4.8 and Figure 4.9). The test
statistic χ2=22.9 (α=.05), df=1, p=.000. The column distributions were not the same. Hypothesis 6
was accepted. There was a difference between the Western and Non-Western culture. The odds of
an extreme score in the Non-Western culture was 2.4 times the odds of an extreme score in the
Western with a 95% CI [1.689 , 3.526]. It was 2.4 times more likely that a person scores an extreme
value in the Non-Western culture than in the Western culture.
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Master Thesis - Lisette Feijen
Table 4.8 Contingency table Internal Locus of Control*Culture
Culture
Western
Internal Locus of
no extreme value
Count
% within Internal
Control
Locus of Control
extreme value
Count
% within Internal
Locus of Control
Count
Total
% within Internal
Locus of Control
NonWestern
Total
172
111
283
60,8%
39,2%
100,0
%
80
126
206
38,8%
61,2%
100,0
%
252
237
489
51,5%
48,5%
100,0
%
n=80
n=126
Figure 4.9 Frequency of extreme scores for ILOC
per Culture
Master Thesis - Lisette Feijen
43
External Locus of Control
To test if there was a cross-cultural difference in the frequency of extreme scores (hypothesis 8) a
Pearson chi-square was calculated to test if the column distributions (frequencies of extreme scores
and no extreme scores) are the same. The percentage of extreme scores in the Western culture is
46.2% and in the Non-Western culture is 53.8%, n=158 (see Table 4.9 and Figure 4.10). The test
statistic χ2=2.7 (α=.05), df=1, p=.103. The column distributions are almost the same. Hypothesis 8
is rejected. There was no difference between the Western and Non-Western culture. The odds of
an extreme score in the Non-Western culture was 1.4 times the odds of an extreme score in the
Western culture with a 95% CI [.938 , 2.006]. It was 1.4 times more likely that a person scores an
extreme value in the Non-Western culture than in the Western culture.
Table 4.9 Contingency table External Locus of Control*Culture
Culture
External Locus of
no extreme value
Locus of Control
extreme value
NonWestern
Total
179
152
331
54,1%
45,9%
100,0
%
73
85
158
46,2%
53,8%
100,0
%
252
237
489
51,5%
48,5%
100,0
%
Count
% within External
Control
Western
Count
% within External
Locus of Control
Count
Total
% within External
Locus of Control
n=73
n=85
Figure 4.10 Frequency of extreme scores for ELOC
per Culture
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Master Thesis - Lisette Feijen
4.3.3 Interaction effect
Internal Locus of Control
To test cross-cultural differences regarding the effect of the number of response categories on the
frequency of extreme scores in ILOC (hypothesis 10) a Cochran chi-square was calculated. This test
statistic of conditional independence Cochran’s χ2=22.1, df=1, p=.000 (N=489). Hypothesis 10 is
accepted. This indicated that there is an association between culture and scale width into the
frequency of extreme scores on ILOC. The manipulation seems to work more extreme among NonWestern cultures, as shown in Figure 4.11 and Figure 4.12. The portion (30%; n=38) of extreme
scores in the wide scale in the Non-Western culture (Figure 4.12) is smaller than this respective
portion (34%; n=27) in the Western culture (Figure 4.11).
n=38
n=27
n=53
Figure 4.11 Frequency of extreme scores for ILOC per scale
width in Western Culture
Master Thesis - Lisette Feijen
n=88
Figure 4.12 Frequency of extreme scores for ILOC per scale
width in Non-Western Culture
45
External Locus of Control
To test cross-cultural differences regarding the effect of the number of response categories on the
frequency of extreme scores in ELOC (hypothesis 12) a Cochran chi-square was calculated. This test
of conditional independence Cochran’s χ2 was 62.9, df=1, p=.000 (N=489). Hypothesis 12 was
accepted. This indicated that there was an association between culture and scale width into the
frequency of extreme scores on ELOC. The manipulation seems to work more extreme among
Western cultures, as shown in Figure 4.13 and Figure 4.14. The portion (15%; n=11) of extreme
scores in the wide scale in the Western culture (Figure 4.13) is smaller than this respective portion
(22%; n=19) in the Non-Western culture (Figure 4.14). The portions of extreme scores in the wide
scale were even smaller in External Locus of Control than in Internal Locus of Control. The
manipulation had even more effect on the frequency of extreme scores in ELOC.
n=11
n=19
n=62
Figure 4.13 Frequency of extreme scores for ELOC per scale
width in Western Culture
46
n=66
Figure 4.14 Frequency of extreme scores for ELOC per scale
width in Non-Western Culture
Master Thesis - Lisette Feijen
4.4 Association between Internal and External Locus of Control
4.4.1 Correlation coefficient
To test if there was a negative association between ILOC and ELOC (hypothesis 13) a Pearson
correlation coefficient was calculated. The Pearson correlation coefficient was based on N=483 of
the rescaled data. There is no significant negative correlation between ILOC and ELOC, the
correlation coefficient r=-.067, p=.072. Hypothesis 13 was rejected. Internal and External Locus of
Control are two independent uncorrelated dimensions.
4.4.2 Cross-cultural differences on the association between Internal and External Locus of Control
In order to test the difference between two independent correlation coefficients (hypothesis 14)
both correlation coefficients and their respectable group size were necessary. In this study there
were two independent samples, namely Western (n=249) and Non-Western (n=234) culture. The
correlation coefficient between ILOC and ELOC in the Western culture was r=-.142, p=.025 (n=249).
There was a negative association between ILOC and ELOC. The correlation coefficient between ILOC
and ELOC in the Non-Western culture r=-.008, p=.901 (n=234). There was no association between
ILOC and ELOC. Fisher’s z-score was computed z=-1.473 (p=.141), hypothesis 14 was accepted.
There was no cross-cultural difference in the association between ILOC and ELOC.
Master Thesis - Lisette Feijen
47
5. Discussion
In this discussion the results of this study are discussed as well as strengths and limitations. Besides,
recommendations for future research are given.
5.1 Results
5.1.1 Number of response categories
The results show a significant effect of the number of response categories on the mean and
frequency of extreme scores. When inspecting the mean and the scores on ILOC and ELOC, it can
be observed that for ILOC the mean scores are around response category 4 and for ELOC this is
around response category 2. From a practical point of view this manipulation will not have major
implications, because the integer does not differ due to the manipulation (despite the statistical
significant difference). However, when integers change due to the manipulation of number of
response categories the practical relevance increases. This research suggests that for LOC and
especially ELOC this could be true, since there is a significant difference. The partial effect size of
ELOC indicated an almost medium effect size with an increase in mean score of 0.4. Using this LOC
scale in practice results in a higher mean score, this is applicable to all respondents and therefore
should be taken into account when comparing this scale with others.
The frequency of extreme scores decreases when the number of response categories increases, as
is consisted with Dawes (2002). This is what you expect, as the variance (number of options) is
increased and the respondents can score high or low at the scale end without scoring on the actual
extreme. However, Clarke III (2001) found that increasing the number of scale categories beyond
five categories had little effect on extreme response. This study shows that there is an effect when
the number of response categories is increased from five to nine. The OR shows that this effect is
quite large for ELOC, 5.8 times more likely to score extreme in a short scale than a wide scale, and
seems to influence External Locus of Control more than Internal Locus of Control. In this study the
operationalization of extreme scores is defined as scoring extreme on either or both items (after
rescaling). Adapting this definition, into for instance scoring extreme on both items, could result
into different results. Also comparing three groups of extreme scores (none, one and both) could
give more insight into differences between extreme scores.
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Master Thesis - Lisette Feijen
5.1.2 Culture
The results show no significant effect of culture on the mean scores of ILOC and ELOC. Perhaps
compressing the heterogeneous sample into two groups was not sufficient for any significant
differences to arise. Another classification of culture could result in different outcomes. However,
culture has a significant effect on the frequency of extreme scores, so the classification made is
sufficient to be detected. The frequency of extreme scores for ILOC are more extreme in the NonWestern Culture. In the Non-Western Culture people tend to agree (score 5) on either of both items
or ILOC (‘I’m my own Boss’ and ‘If I work hard, I will succeed’), this could indicate that there might
be a sort of acquiescence for ILOC in the Non-Western Culture. This is also claimed by Smith (2004)
who refers to the in-group harmony in collectivist countries which might lead to acquiescence.
Whereas Non-Westerners are known to be more externally oriented (score higher on ELOC)
(Hamamura et al., 2008) and overall are perceived to have a more moderate response style
(Hamamura et al., 2008; Harzing, 2006). From this perspective you would expect moderate mean
scores on ILOC within Non-Western Culture and not significantly more extreme scores (as found).
This reasoning is also supported by the idea that Westerners are considered to be less concerned
with the consequences of expressing strong opinions and thus extreme response style (Harzing,
2006; Johnson, 2005). However, Johnson (2005) found similar results as in this study with a
heterogeneous sample of adults from 19 countries. This would support the results from this study
in another heterogeneous sample.
5.1.3 Moderating effect of Culture
Culture has no significant moderating effect on the effect of the number of response categories on
the mean. Both cultures are equally sensitive to the manipulation of number of response categories.
This would mean that the 4-item LOC scale can be applied cross-culturally to measure LOC.
However, this is only the case for the classification of culture in this study. Another classification
could result in different outcomes when investigating moderating effects of culture on the number
of response categories.
The inspection of both dependent variables (separately) with regard to the frequency of
extreme scores it is apparant that Internal Locus of Control is affected (with a significant p-value)
by both #RC, culture, and their interplay. External Locus of Control is significantly affected by the
number of response categories and the moderating effect of Culture. This moderating effect
differed in each Culture. From this we can derive that the number of response categories has a
stronger influence or a larger effect on the frequency of extreme scores than a single effect of
Master Thesis - Lisette Feijen
49
culture. The interesting feature of this study is the moderating effect of culture on the frequency of
extreme scores.
There is a significant moderating effect of culture on the effect of the number of response
categories on the frequency of extreme scores in ILOC and ELOC. This moderating effect shows that
the manipulation of scale width is more extreme in ILOC in the Non-Western culture and more
extreme in ELOC in the Western culture. When the number of response categories increase the
frequency of extreme scores decreases. This phenomenon is more extreme for ILOC in the NonWestern culture and for ELOC even more extreme in the Western culture. Using more response
categories would have less possible acquiescence on ILOC for the Non-Western culture, since NonWesterners score significantly less extreme on ILOC then Westerners when more response
categories are used. Therefore using more response categories would result in lower acquiescence
in ILOC.
5.1.4. Association ILOC and ELOC
Based on Kovaleva (2012) it was expected that there is a negative association between ILOC and
ELOC. However, this study reveals that this hypothesis could not be accepted. The null hypothesis
that there is no association was not rejected and therefore accepted. This would entail that Internal
Locus of Control and External Locus of Control are two separate orthogonal dimensions, as
presented by other authors (Lefcourt, 1972; Levenson, 1972; Wallston et al., 1978). On the other
hand, this study did not perform a Confirmatory Factor Analysis to determine the factor structure,
instead an Exploratory Factor Analysis (PAF) is used. However, when investigating this association
between ILOC and ELOC for each dominant culture, which is part of the test of the difference
between two independent correlation coefficients (Preacher, 2002), there is a difference. In the
Western culture there is a significant negative association between ILOC and ELOC while in the
Non-Western culture there is not. This has implications on the factor structure, since there is a two
correlated factors structure in the Western Culture and a two uncorrelated factor structure in the
Non-Western culture. Using the 4-item LOC scale would therefore have other interpretations in
practice dependent on dominant culture.
50
Master Thesis - Lisette Feijen
5.2 Strengths
The sample consists of two heterogeneous independent samples. One sample received the original
4-items LOC scale (5 response categories) as part of a larger questionnaire, the other sample
received the same questionnaire with the manipulation (9 response categories). The number of
respondents and the recruitment of respondents is based on course registration. The researcher
has no influence on this. With regard to the questionnaire the course registration has a role as well.
Based on the enrolment for either of the two courses the exact number of questionnaires can be
printed and prepared, also the distribution of version (order 1 and order 2) is equal for each course.
This results in a balanced distribution of versions of the questionnaire. Besides this, the
questionnaire is handed out by the teacher of the course and not by the researcher. There is more
familiarity with the teacher than an outside researcher, so there will be less a ‘guinea-pig’ effect.
Respondents have less the idea that they are a test subject when a familiar teacher asks them to fill
in a questionnaire compared to an non-familiar outsider. Therefore it is expected that respondents
are more authentic in answering the questions although it is already anonymous. Lastly, the
classification process in this study is based on existing research like Tobi and Kampen (2013) whom
handled similar data from the same questionnaire in a previous research.
5.3 Limitations
The sample consists solely of students of Wageningen University and this has an influence on the
external validity. These students are not representative for their country of origin and therefore
culture. A limited age group is included in the sample and students are highly educated people.
Other levels of education are not represented in the sample. Besides this, one can deliberate if
highly educated people express Internal LOC and/or External LOC differently than not higheducated people. Perhaps high-educated are in general more Internal and/or more inclined to have
an extreme response style. This feature is not included in this study. The process of distribution of
the questionnaires is dependent on the teacher. Therefore instructions need to be clear and trust
that the teacher distributes the questionnaires as intended. This also related to the distribution of
version. In 2014 when the wide scale was distributed the distribution of version is similar, but in
2013 (short scale) there is a large difference in versions. There is a difference of 40 questionnaires
between order 1 and order 2. This could have an impact on the 2 x 2 x 2 design. The group sizes in
the cells of the design could differ too much, which can affect the homogeneity of variances (on
the analysis assumptions). Lastly, the labelling of the response categories. In this study the labelling
of the response categories differed, the short scale has labelling at every scale point while the wide
scale has labelling at the ends. This is a confounder that could not be measured nor corrected for
in this study. Therefore we cannot say with absolute certainty that the effect of the number of
Master Thesis - Lisette Feijen
51
response categories is due to the number of response categories. However, there is some evidence
on the use and omission of mid-points. Mid-points have no effect on the mean of the response
levels (Si & Cullen, 1998 cited by Dawes, 2002) and omission of a mid-point mainly effects the
frequencies of the neighbouring response categories (Spagna, 1984 cited by Dawes, 2002). The
confounding effect of labelling could be less influential than anticipated.
5.4 Recommendations
Cross-cultural analysis in the frequencies of extreme scores can be expanded by including more
levels of extreme response and compare extreme response with moderate response. Also, a
distinction between extreme scores at the different ends can be made to gain insight on
acquiescence and disacquiescence. This would result in differences in extreme scores between
Cultures at each scale end, such as more extreme scores at low end for ELOC in Western Culture.
Future research can also focus on excluding labelling as a possible confounder for the effect of the
number of response categories, comparing a 5-point scale with a 9-point scale.
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Master Thesis - Lisette Feijen
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7. Appendices
Appendix I – Questionnaire
Appendix II – Syntax for SPSS
Syntax 1 - Correction for version
Syntax 2 – Calculation of ILOC and ELOC
Syntax 3 – Correction for scale width (via recoding)
Syntax 4 – Calculation scale scores ILOC and ELOC
Syntax 5 – Extreme scores
Syntax 6 – recode in no extreme and extreme score
Appendix III – Output Results
Principal Axis Factoring
Correlations (Inter-item, Item-whole and Dimensions)
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Appendix I – Questionnaire
At Wageningen University many different students take one of our courses in Research
Methodology. To get a better insight in the students who take this particular course, we would
like to invite you to answer the questions below. Please, be so kind as to fill in this
questionnaire. It will only take about 5 minutes.
1. What is the code of your MSc-programme? Please, answer the question by circling the
number in front of the correct answer.
1. MAB
6. MBT
11. MFQ
16. MID
21. MME
26. MPS
2. MAF
7. MCS
12. MFS
17. MIL
22. MMS
27. MSS
3. MAS
8. MEA
13. MFT
18. MLE
23. MNH
28. MUE
4. MBF
5. MBI
9. MES
10. MFN
14. MGI
15. MHW
19. MLP
20. MMA
24. MOA
25. MPB
29. Other
2. In a typical week, how many hours do you spend on this course (YRM20806) including
classes? Please circle the answer that is most appropriate for you.
(1)
< 5 hrs
(2) 6 - 10 hrs
(3) 11 - 15 hrs
(4) 16 - 20 hrs
(5) > 20 hrs
3. Will you consider taking any of the following research methodology modules in ACT
(Academic Consultancy Training)? Please, circle the correct answer.
Interview techniques
(1) yes
Observation techniques
(1) yes
Questionnaire construction (1) yes
(2) no
(2) no
(2) no
(3) don’t know
(3) don’t know
(3) don’t know
4. How satisfied are you with working in groups in general? Please, circle the number
that best reflects your answer.
Not at all
satisfied
1
2
3
4
5
6
7
8
Extremely
satisfied
9
5. How satisfied are you with working in groups in this course? Please, circle the number
that best reflects your answer.
Not at all
satisfied
1
2
3
4
5
6
7
8
Extremely
satisfied
9
6. How would you rate your ability? Please, circle the correct number.
a. to speak English?
b. to understand spoken English?
c. to read English?
d. to write English?
Master Thesis - Lisette Feijen
Excellent Good Fair Poor
(4)
(3)
(2)
(1)
(4)
(3)
(2)
(1)
(4)
(3)
(2)
(1)
(4)
(3)
(2)
(1)
57
7. Did you take the Test Of English as a Foreign Language (TOEFL)?
(1) No
(2) Yes, my score was ……..
8. What is your first language?
……………………………………..
9. What is your second language? ……………………………………..
10.
What is your third language?
..……………………………………
11.
Do you consider yourself bi-lingual or multi-lingual? Please circle the correct answer.
(1) No, monolingual
(2) Yes, bilingual
(3) Yes, with three or more languages
12.
Which language did/do you speak with your parents/caretakers?
…………………………………………………….
13.
Which was/were the language(s) of instruction at your high school?
………………………………………….………..…………………………………………………….
The following statements may apply more or less to you. To what extent do you think each
statement applies to you personally.
Doesn't
apply at all
Applies
completely
14. I'm my own boss.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
15. If I work hard, I will succeed.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
16. Whether at work or in my private
life: what I do is mainly
determined by others.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
17. Bad luck often gets in the way of
my plans.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
18.
What is your country of origin? ……………………………………….
19.
How long have you been living in the Netherlands? Please, circle the correct answer.
(1)
(2)
(3)
(4)
Less than 6 months
Between 6 and 12 months
Between 1 and 2 years
More than 2 years
20.
What is your age? ……….. years
21.
What is your gender? Please, circle the correct answer.
(1) male
(2) female
Thank you for your cooperation!
58
Master Thesis - Lisette Feijen
The questionnaire on the previous page had order 1. Order 2 had different ordering in these
questions below. Except for question 2, the scales in the answers options differed, and question 10
where the order of response categories differed.
2. In a typical week, how many hours do you spend on this course (YRM20806) including
classes? Please circle the answer that is most appropriate for you.
(1)
< 20 hrs
(2) 21 - 25 hrs
(3) 26 - 30 hrs
(4) 31 - 35 hrs
(5)
> 35 hrs
8. How satisfied are you with working in groups in this course? Please, circle the number
that best reflects your answer.
Not at all
satisfied
1
2
3
4
5
6
7
8
Extremely
satisfied
9
9. How satisfied are you with working in groups in general? Please, circle the number
that best reflects your answer.
Not at all
satisfied
1
2
3
4
5
6
7
8
Extremely
satisfied
9
10. How would you rate your ability? Please, circle the correct number.
Excellent Good Fair Poor
(1)
(2)
(3)
(4)
(1)
(2)
(3)
(4)
(1)
(2)
(3)
(4)
(1)
(2)
(3)
(4)
a. to speak English?
b. to understand spoken English?
c. to read English?
d. to write English?
The following statements may apply more or less to you. To what extent do you think each
statement applies to you personally.
Doesn't
apply at all
Applies
completely
14. I'm my own boss.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
15. Bad luck often gets in the way of
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
my plans.
16. Whether at work or in my private
life:
what
I
do
is
mainly
determined by others.
17. If I work hard, I will succeed.
Master Thesis - Lisette Feijen
59
Appendix II – Syntax for SPSS
Syntax 1 - Correction for version
If (version=1) General = Q4.
If (version=1) Group = Q5.
If (version=2) Group = Q4.
If (version=2) General = Q5.
FREQUENCIES VARIABLES=General, Group.
If (version=1) BOSS = Q14.
If (version=1) SUCCEED = Q15.
If (version=1) OTHERS = Q16.
If (version=1) FATE = Q17.
If (version=2) BOSS = Q14.
If (version=2) FATE = Q15.
If (version=2) OTHERS = Q16.
If (version=2) SUCCEED = Q17.
FREQUENCIES VARIABLES=BOSS, Succeed, Others, fate.
Syntax 2 – Calculation of ILOC and ELOC
IF (BOSS ge 1 AND SUCCEED ge 1) Int_LOC=mean(BOSS, SUCCEED).
IF ( Others ge 1 and fate ge 1) Ext_LOC=mean(Others, fate).
EXAMINE VARIABLES=Int_LOC, Ext_LOC
/PLOT NONE
/STATISTICS DESCRIPTIVES
/CINTERVAL 95
/MISSING PAIRWISE
/NOTOTAL.
Syntax 3 – Correction for scale width (via recoding)
DO IF (Year = 4).
RECODE BOSS SUCCEED OTHERS FATE (1=1) (2=2) (3=3) (4=4) (5=5) INTO Boss_rescaled
Succeed_rescaled
Others_rescaled BadLuck_rescaled.
END IF.
VARIABLE LABELS Boss_rescaled 'Boss_rescaled' /Succeed_rescaled 'Succeed_rescaled'
/Others_rescaled 'Others_rescaled' /BadLuck_rescaled 'BadLuck_rescaled'.
EXECUTE.
DO IF (Year = 5).
RECODE BOSS SUCCEED OTHERS FATE (1=1) (2=1.5) (3=2) (4=2.5) (5=3) (6=3.5) (7=4) (8=4.5) (9=5)
INTO
Boss_rescaled Succeed_rescaled Others_rescaled BadLuck_rescaled.
END IF.
VARIABLE LABELS Boss_rescaled 'Boss_rescaled' /Succeed_rescaled 'Succeed_rescaled'
/Others_rescaled 'Others_rescaled' /BadLuck_rescaled 'BadLuck_rescaled'.
EXECUTE.
60
Master Thesis - Lisette Feijen
Syntax 4 – Calculation scale scores ILOC and ELOC
IF (Boss_rescaled ge 1 and Succeed_rescaled ge 1) Internal_LOC=mean(Boss_rescaled,
Succeed_rescaled).
IF (Others_rescaled ge 1 and BadLuck_rescaled ge 1) External_LOC=mean(Others_rescaled,
BadLuck_rescaled).IF (Boss_rescaled ge 1 and Succeed_rescaled ge 1).
COMPUTE Internal_LOC=MEAN(Boss_rescaled, Succeed_rescaled).
IF (Boss_rescaled ge 1 and Succeed_rescaled ge 1).
VARIABLE LABELS Internal_LOC 'COMPUTE Internal_LOC=MEAN(Boss_rescaled, Succeed_rescaled)'.
EXECUTE.
COMPUTE External_LOC=MEAN(Others_rescaled, BadLuck_rescaled).
IF (Others_rescaled ge 1 and BadLuck_rescaled ge 1).
VARIABLE LABELS External_LOC 'COMPUTE EXternal_LOC=MEAN(Others_rescaled, BadLuck_rescaled)'.
EXECUTE.
Syntax 5 – Extreme scores
RECODE Boss_rescaled Succeed_rescaled Others_rescaled BadLuck_rescaled (1=1) (5=1)
(SYSMIS=SYSMIS)
(1.5 thru 4.5=0) INTO Boss_Extreme Succeed_Extreme Others_Extreme BadLuck_Extreme.
VARIABLE LABELS Boss_Extreme 'Boss_Extreme' /Succeed_Extreme 'Succeed_Extreme' /Others_Extreme
'Others_Extreme' /BadLuck_Extreme 'BadLuck_Extreme'.
EXECUTE.
IF (Society >= 1) Internal_Extreme=SUM(Boss_Extreme,Succeed_Extreme).
VARIABLE LABELS Internal_Extreme 'IF (Society >= 1) '+
'Internal_Extreme=SUM(Boss_Extreme,Succeed_Extreme) '.
EXECUTE.
IF (Society >= 1) External_Extreme=SUM(Others_Extreme,BadLuck_Extreme).
VARIABLE LABELS External_Extreme 'IF (Society >= 1) '+
'External_Extreme=SUM(Others_Extreme,BadLuck_Extreme) '.
EXECUTE.
Syntax 6 – recode in no extreme and extreme score
DO IF (Society >= 1).
RECODE Internal_Extreme External_Extreme (0=0) (SYSMIS=SYSMIS) (1=1) (2=1) INTO
ILOC_Extreme_yes_no
ELOC_Extreme_yes_no.
END IF.
VARIABLE LABELS ILOC_Extreme_yes_no 'ILOC_Extreme_yes_no' /ELOC_Extreme_yes_no
'ELOC_Extreme_yes_no'.
EXECUTE.
Master Thesis - Lisette Feijen
61
Appendix III – Output from SPSS
Principal Axis Factoring
Total Sample
Total Variance Explained
Rotation Sums of
Squared
Initial Eigenvalues
Factor
Total
% of Variance
Loadingsa
Extraction Sums of Squared Loadings
Cumulative %
Total
% of Variance
Cumulative %
Total
1
1,402
35,038
35,038
,759
18,966
18,966
,743
2
1,207
30,166
65,204
,573
14,317
33,283
,611
3
,767
19,180
84,384
4
,625
15,616
100,000
Extraction Method: Principal Axis Factoring.
a. When factors are correlated, sums of squared loadings cannot be added to obtain a total variance.
Factor Correlation Matrix
Pattern Matrixa
Factor
1
Boss_rescaled
2
,096
,647
-,091
,422
Others_rescaled
,442
-,059
BadLuck_rescaled
,728
,074
Succeed_rescaled
Extraction Method: Principal Axis Factoring.
Rotation
Method:
Oblimin
with
Factor
1
2
1
1,000
-,172
2
-,172
1,000
Extraction Method: Principal Axis
Factoring.
Rotation Method: Oblimin with
Kaiser Normalization.
Kaiser
Normalization.a
a. Rotation converged in 4 iterations.
62
Master Thesis - Lisette Feijen
Western Culture
Total Variance Explaineda
Rotation Sums of
Squared
Initial Eigenvalues
Factor
Total
% of Variance
Loadingsb
Extraction Sums of Squared Loadings
Cumulative %
Total
% of Variance
Cumulative %
Total
1
1,482
37,050
37,050
,809
20,225
20,225
,716
2
1,117
27,933
64,983
,421
10,525
30,749
,619
3
,756
18,900
83,883
4
,645
16,117
100,000
Extraction Method: Principal Axis Factoring.
a. Only cases for which Society = Western are used in the analysis phase.
b. When factors are correlated, sums of squared loadings cannot be added to obtain a total variance.
Pattern Matrixa,b
Factor Correlation Matrixa
Factor
1
2
Factor
1
2
1
1,000
-,281
2
-,281
1,000
Boss_rescaled
,584
-,077
Succeed_rescaled
,568
,054
Extraction Method: Principal Axis
Others_rescaled
-,001
,610
Factoring.
BadLuck_rescaled
-,002
,421
Rotation Method: Oblimin with
Extraction Method: Principal Axis Factoring.
Kaiser Normalization.
Rotation
a. Only cases for which Society =
Method:
Oblimin
with
Kaiser
Normalization.
Western are used in the analysis
a. Rotation converged in 4 iterations.
phase.
b. Only cases for which Society = Western are
used in the analysis phase.
Master Thesis - Lisette Feijen
63
Non-Western Culture
Total Variance Explaineda
Rotation Sums of
Squared
Initial Eigenvalues
Factor
Total
% of Variance
Loadingsb
Extraction Sums of Squared Loadings
Cumulative %
Total
% of Variance
Cumulative %
Total
1
1,441
36,034
36,034
1,002
25,041
25,041
,999
2
1,254
31,357
67,391
,622
15,555
40,595
,622
3
,770
19,245
86,636
4
,535
13,364
100,000
Extraction Method: Principal Axis Factoring.
a. Only cases for which Society = Non-Western are used in the analysis phase.
b. When factors are correlated, sums of squared loadings cannot be added to obtain a total variance.
Factor Correlation Matrixa
Pattern Matrixa,b
Factor
1
Boss_rescaled
2
,157
,672
-,151
,414
Others_rescaled
,432
-,045
BadLuck_rescaled
,883
,087
Succeed_rescaled
Extraction Method: Principal Axis Factoring.
Rotation
Method:
Oblimin
with
Kaiser
Normalization.
a. Rotation converged in 3 iterations.
Factor
1
2
1
1,000
-,105
2
-,105
1,000
Extraction Method: Principal Axis
Factoring.
Rotation Method: Oblimin with
Kaiser Normalization.
a. Only cases for which Society =
Non-Western are used in the
analysis phase.
b. Only cases for which Society = Non-Western
are used in the analysis phase.
64
Master Thesis - Lisette Feijen
Correlations
Inter-Items correlations and Item-whole correlations
Correlations
Boss_rescal Succeed_re Others_resc BadLuck_re
ed
Boss_rescaled
scaled
,000
486
,275**
1
Sig. (1-tailed)
Succeed_rescaled
Others_rescaled
BadLuck_rescaled
Internal
Locus
Control
External
Control
Locus
Pearson Correlation
Sig. (1-tailed)
,000
N
485
Pearson Correlation
scaled
-,056
Pearson Correlation
N
aled
,275**
Internal
External
Locus of
Locus of
Control
Control
,047
,857**
-,007
,110
,150
,000
,443
485
485
485
485
484
1
-,060
-,105*
,730**
-,105*
,094
,010
,000
,010
486
486
485
485
1
,336**
-,077*
,798**
,000
,046
,000
488
-,056
-,060
Sig. (1-tailed)
,110
,094
N
485
486
488
487
484
487
Pearson Correlation
,047
-,105*
,336**
1
-,027
,836**
Sig. (1-tailed)
,150
,010
,000
,279
,000
N
485
486
487
488
484
487
,857**
,730**
-,077*
-,027
1
-,067
Sig. (1-tailed)
,000
,000
,046
,279
N
485
485
484
484
485
483
-,007
-,105*
,798**
,836**
-,067
1
Sig. (1-tailed)
,443
,010
,000
,000
,072
N
484
485
487
487
483
of Pearson Correlation
of Pearson Correlation
,072
487
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
Correlation between ILOC and ELOC
Correlations
Internal Locus of Control
Pearson Correlation
Internal Locus of
External Locus
Control
of Control
1
Sig. (1-tailed)
N
External Locus of Control
Pearson Correlation
,072
485
483
-,067
1
Sig. (1-tailed)
,072
N
483
Master Thesis - Lisette Feijen
-,067
487
65