A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
Supplemental Materials
Gender Differences in Response to Competition With Same-Gender Coworkers: A
Relational Perspective
by S. Y. Lee et al., 2016, Journal of Personality and Social Psychology
http://dx.doi.org/10.1037/pspi0000051
Table of Contents
Part 1. Additional analyses to investigate the moderating effect of cooperation strength on
coworker liking in Study 1
Part 2. Comparisons of predicted and reverse mediational models for Studies 2, 3, and 4
Part 3. Analyses of relational damage after the second round in Study 3 and in Study 4
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A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
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Part 1. Additional analyses to investigate moderating the effect of cooperation strength
on coworker liking in Study 1
We conducted additional analyses to ascertain whether the moderating effect of
competition intensity is distinct from the effect of cooperation strength. The 3-way interaction
between participant gender, coworker gender, and competition intensity remained marginally
significant after including cooperation strength as a moderator in the analysis (p = .063). That
is, when we added a main effect of cooperation strength (mean-centered by participant), its 2way interactions, 3-way interactions, and the 4-way interaction to the multi-level model
reported in the manuscript, the 3-way interaction among competition intensity, participant
gender, and coworker gender was marginally significant (b = -1.80, SE = 0.95), t(1, 88.07) = 1.88, p = .063. In this model, the only other coefficient to reach marginal significance was a
main effect of cooperation strength b = 0.54, SE = 0.28), t(1, 186.79) = 1.94, p = .054.
Cooperation strength thus did not significantly moderate the relationship between coworker
gender and liking.
Table S1 presents the results of the multi-level regression analysis of coworker liking
on participant gender, coworker gender, competition intensity, cooperation strength, and all
their interactions.
Table S2 presents the results of the multi-level regression analyses of coworker liking
on coworker gender and cooperation strength, separately for female and male participants.
Table S1
Study 1: Additional Multi-Level Regression Analysis of Coworker Liking
Variables
b
SE
A: Participant gender (1 = female, 0 = male)
-0.22
0.19
B: Coworker gender (1 = same, 0 = opposite)
-0.06
0.14
C: Competition intensity
0.10
0.32
†
D: Cooperation strength
0.54
0.28
A×B
0.05
0.21
A×C
-0.13
0.47
A×D
-0.34
0.40
t (df)
-1.13 (1, 186.8)
-0.42 (1, 94.9)
0.32 (1, 186.8)
1.94 (1, 186.8)
0.26 (1, 99.5)
-0.28 (1, 186.8)
-0.84 (1, 186.8)
A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
B×C
B×D
C×D
A×B×C
A×B×D
A×C×D
B×C×D
A×B×C×D
Intercept
-0.33
0.37
-0.52
-1.80†
0.85
-0.45
0.25
2.14
5.67***
0.63
0.50
0.50
0.95
0.72
0.85
0.74
1.32
0.14
3
-0.52 (1, 92.9)
0.74 (1, 125.8)
-1.04 (1, 186.8)
-1.88 (1, 88.1)
1.18 (1, 124.8)
-0.53 (1, 186.8)
0.33 (1, 52.5)
1.62 (1, 42.3)
41.87 (1, 186.8)
Note. Coworker liking is the dependent variable. Competition intensity and cooperation
strength are mean-centered by participant. Values are unstandardized regression coefficients.
All tests are two-tailed.
†
p < .10.
***
p < .001.
Table S2
Study 1: Additional Multi-Level Regression Analyses of Same- and Opposite-Gender
Coworker Liking on Cooperation Strength, Separately for Female and Male Participants
Female Participants
Male Participants
t (df)
t (df)
Variables
b
SE
b
SE
A: Coworker gender
0.15
0.20 0.74 (53.8)
-0.07
0.12 -0.61 (67.0)
(1 = same, 0 = opposite)
B: Cooperation strength
0.27
0.32 0.84 (83.5)
0.61*
0.26 2.32 (102.8)
†
A×B
1.19
0.70 1.69 (44.1)
0.25
0.47
0.53 (57.1)
Intercept
0.15
***
5.46
36.84
(83.5)
5.64***
0.12
46.00 (102.8)
Note. Coworker liking is the dependent variable. Cooperation strength is mean-centered by
participant. Values are unstandardized regression coefficients. All tests are two-tailed.
†
p < .10.
*
p < .05.
***
p < .001.
A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
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Part 2. Comparisons of predicted and reverse mediational models for Studies 2, 3, and 4
To compare predicted (i.e., hypothesized) and reverse mediational models in Studies
2, 3, and 4, we conducted structural equation model (SEM) analyses using SPSS AMOS.
Following prior research (Hu & Bentler, 1999; Kline, 2010), the model fits of
predicted and reverse mediation models were estimated using chi-squared tests1 (the smaller,
the better; the larger p-value, the better), root mean square error (RMSEA; a cutoff of .08 and
the smaller, the better), goodness-of-fit index (GFI; a cutoff of .90 and the closer to 1, the
better), normed fit index (NFI; a cutoff of .90 and the closer to 1, the better), and comparative
fit index (CFI; a cutoff of .90 and the closer to 1, the better).
Details of the SEM analyses and model comparisons between predicted and reverse
mediational models for each of Studies 2, 3, and 4 are presented below.
Study 2
Figure S1 illustrates the hypothesized and reverse mediation models for Study 2 we
compared using SEM analyses.
The chi-squared test indicated significance for the hypothesized mediation model, χ2 =
28.09, p < .001, and non-significance for the reverse mediation model, χ2 = 3.39, p = .336.
Chi-square comparisons between the models suggest that the predicted mediation model had a
poorer fit, ∆χ2(3) = 24.70, p < .001. RMSEA indices also showed that the predicted mediation
model had a poorer fit (RMSEA predicted = .15 > RMSEA reverse = .02). In terms of GFI, NFI,
and CFI indices, both models were shown to have relatively good fits to the data (please see
Table S3 for details of all model fit indices and model comparisons).
Altogether, these results suggest that the reverse mediation model has a better fit than
the predicted mediation model in Study 2.
1
Chi-square test is a limited measure of fit for samples with N smaller than 400 (for details see Kline,
2010; Steiger, 2007). We thus also consider a set of other model fit indices.
A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
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Figure S1
Study 2: The hypothesized mediation model (in line with Hayes, 2013, Process Model 7)
Study 2: The reverse mediation model (in line with Hayes, 2013, Process Model 7)
Table S3
Study 2: Fit Indices and Model Comparisons
Model
Structural equation model:
Fit indices
2
χ
df RMSEA GFI NFI
CFI
Predicted mediation
28.09*** 3
.15
.97
.95
.96
Reverse mediation
3.39
3
.02
.99
.99
.99
Model
comparison
∆ χ2(3)
24.70***
Note. N = 352. RMSEA: root mean square error; GFI: goodness-of-fit index; NFI: normed fit
index; CFI: comparative fit index.
***
p < .001.
Study 3
Figure S2 illustrates the hypothesized and reverse mediation models for Study 3 we
compared using SEM analyses.
The chi-squared test indicated non-significance for both the hypothesized mediation
model, χ2 = 13.90, p = .307, and the reverse mediation model, χ2 = 8.80, p = .720. Chi-square
comparisons between the models suggest that the two models were not significantly different
in terms of model fits, ∆ χ2(12) = 5.01, n.s. However, the smaller chi-square of the reverse
mediation model suggests that it has a better model fit than the predicted mediation model.
RMSEA indices also showed that the reverse mediation model had a better fit (RMSEA predicted
A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
= .03 larger than RMSEA reverse < .01), although RMSEA indices of both models were under
the cutoff level of .08. In terms of GFI, NFI, and CFI indices, both models were shown to
have relatively good fits to the data (please see Table S4 for details of all model fit indices
and model comparisons).
Altogether, these results suggest that the reverse mediation model has a better fit than
the predicted mediation model in Study 3.
Figure S2
Study 3: The hypothesized mediation model (in line with Hayes, 2013, Process Model 11)
Study 3: The hypothesized mediation model (in line with Hayes, 2013, Process Model 11)
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A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
Table S4
Study 3: Fit Indices and Model Comparisons
Model
Structural equation model:
Fit indices
2
χ
df RMSEA GFI NFI
CFI
Predicted mediation
13.90
12
.03
.99
.99
.99
Reverse mediation
8.80
12
.00
.99
.99
1.00
7
Model
comparison
∆ χ2(12)
5.01
Note. N = 214. RMSEA: root mean square error; GFI: goodness-of-fit index; NFI: normed fit
index; CFI: comparative fit index.
Study 4
Figure S3 illustrates the hypothesized and reverse mediation models for Study 4 we
compared using SEM analyses.
The chi-squared test indicated significance for the hypothesized mediation model, χ2 =
10.76, p = .013, and non-significance for the reverse mediation model, χ2 = 3.66, p = .301.
Chi-square comparisons between the models suggest that the predicted mediation model had a
poorer fit, but the significance was marginal, ∆ χ2(3) = 7.01, p < .10. RMSEA indices also
showed that the predicted mediation model had a poorer fit (RMSEA predicted = .16 > RMSEA
reverse =
.05). In terms of GFI, NFI, and CFI indices, both models were shown to have
relatively good fits to the data (please see Table S5 for details of all model fit indices and
model comparisons).
Altogether, these results suggest that the reverse mediation model has a better fit than
the predicted mediation model in Study 4.
Figure S3
Study 4: The hypothesized mediation model (in line with Hayes, 2013, Process Model 7)
A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
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Study 4: The reverse mediation model (in line with Hayes, 2013, Process Model 7)
Table S5
Study 4: Fit Indices and Model Comparisons
Model
Structural equation model:
Fit indices
χ2
df RMSEA GFI NFI
CFI
*
Predicted mediation
10.76
3
.16
.96
.93
.95
Reverse mediation
3.66
3
.05
.99
.98
.99
Model
comparison
∆ χ2 (3)
7.10+
Note. N = 104. RMSEA: root mean square error; GFI: goodness-of-fit index; NFI: normed fit
index; CFI: comparative fit index.
+
p < .10.
*
p < .05.
A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
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Part 3. Analyses of relational damage after the second round in Study 3 and in Study 4
Study 3
In Study 3, all participants performed a second round of the typing task and answered
the items measuring subsequent relational damage. This second round was included in the
study design to explore whether the effect of a competitive interaction would carry over to a
subsequent cooperative interaction. We present below methodological details of this part of
the study and the results for the subsequent relational damage measure.
Methods
In the second round, all pairs worked under cooperative interdependence. The
experimenter told participants that they would cooperate in the second round of the task (3
probes), and their chances to win the prize draw would be contingent on their joint
performance. The experimenter gave participants predetermined performance feedback after
each probe: They were told that their joint performance was above the threshold in the first
and last probes, and they both failed to perform above the threshold in the second probe.
After completing the second round of the task, participants were again led to
individual rooms where they answered the seven items of the subsequent relational damage
(α = .82) measure in an online survey. The seven items of this measure were identical to those
completed after the first round. All participants were debriefed and got a chance to report any
suspicions. None of them did.
Results
We examined whether the negative effect of competition would carry over to a
subsequent cooperative task. On balance, the results do not support this possibility.
A 2 × 2 × 2 analysis of variance (ANOVA) revealed a marginally significant main
effect of participant gender, F(1, 206) = 3.32, p = .07, ηp2 = .02, and a significant interaction
effect between participant gender and coworker gender, F(1, 206) = 7.44, p = .007, ηp2 = .03
A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
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(all the other effects were non-significant, ps > .265). The lack of a significant 3-way
interaction effect (p = .544) suggests that the negative effect of competition on female-female
work relationships did not persist after cooperation was induced.
We conducted a set of simple effects analyses to understand the unexpected 2-way
interaction between participant gender and coworker gender. Regardless of initial
interdependence, female participants reported a higher level of relational damage (M = 2.58,
SD = 0.90) than male participants did with their same-gender coworker (M = 2.10, SD =
0.66), F(1, 104) = 9.96, p = .002, ηp2 = .09. Participant gender had no effect on relational
damage with an opposite-gender coworker (M female = 2.21, SD female = 0.73; M male = 2.31, SD
male
= 0.79), F(1, 106) = 0.47, p = .493, ηp2 = .004.
Study 4
In Study 4, as in Study 3, all participants performed a second round of the dot-
estimation task and then answered the items measuring subsequent relational damage. We
present below methodological details on this part of the study and the results for the
subsequent relational damage measure.
Methods
In the second round, all pairs worked under cooperative interdependence. The
experimenter told participants that they would cooperate in the second round of the task (3
probes), and their chances to win the prize draw would be contingent on their joint
performance. As in the second round of Study 3, participants were told that their joint
performance was above the threshold in the first and last probes, and they both failed to
perform above the threshold in the second probe.
After completing the second round of the task, participants were led to individual
rooms where they answered the seven items of the subsequent relational damage measure (α
= .82) in an online survey (identical to those completed after the first round). After
A RELATIONAL PERSPECTIVE ON SAME-GENDER COMPETITION
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participants performed one unrelated study, they were debriefed and got a chance to report
any suspicions. None of them did.
Results
We examined whether the negative effect of competition would carry over to a
subsequent cooperative task. The results provide support for this possibility.
A 2 × 2 ANOVA revealed no main effects (ps > .117) but a significant interaction
effect between participant gender and initial interdependence, F(1, 100) = 13.90, p < .001, ηp2
= .12.
Simple effects analyses showed that female participants reported a higher level of
subsequent relational damage if they had initially competed (M = 2.51, SD = 0.61) rather than
cooperated (M = 1.81, SD = 0.47) with a same-gender coworker, F(1, 54) = 23.21, p < .001,
ηp2 = .30. In contrast, male participants did not report significantly different levels of
subsequent relational damage whether they had initially cooperated (M = 2.46, SD = 0.93) or
competed (M = 2.18, SD = 0.60) with a same-gender coworker, F(1, 46) = 1.53, p = .22, ηp2 =
.03.
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References for Supplementary Materials
Hayes, A. F. (2013). Introduction to Mediation, Moderation, and Conditional Process
Analysis: A Regression-Based Approach. New York, NY: The Guilford Press.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure
analysis: Conventional criteria versus new alternatives. Structural Equation Modeling,
6(1), 1–55. doi: 10.1080/10705519909540118
Kline, R. B. (2010). Principles and practice of structural equation modeling. New York, NY:
Guilford Press.
Steiger, J. H. (2007). Understanding the limitations of global fit assessment in structural
equation modeling. Personality and Individual Differences, 42(5), 893–898. doi:
10.1016/j.paid.2006.09.017