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Copyright 1990 by the American Psychological Association, Inc.
0033-2909/90/S00.75
Psychological Bulletin
1990. Vol. 107, No. 2, 226-237
Growing Up and Growing Apart: A Developmental
Meta-Analysis of Twin Studies
Kathleen McCartney
Monica J. Harris
University of Kentucky
University of New Hampshire
Frank Bernieri
Oregon State University
Developmental change in twin similarity was examined with age contrasts in a meta-analysis of twin
studies from 1967 through 1985. Intraclass re were coded from 103 papers that included data for
monozygotic or dizygotic twins, or for both, on personality or intelligence variables. Analyses indicated that there was a general tendency for some intraclass rs to decrease with age. In other words,
as twins grow up, they grow apart. There were also developmental differences associated with components of variance for heritability, the shared environment, and the nonshared environment. Mechanisms through which the nonshared environment may operate are discussed.
The purpose of this article is twofold. First, we offer meta-
meta-analysis include (a) obtaining a combined estimate from
analysis as a tool for developmental hypothesis testing. The field
of developmental psychology is often criticized for being not a
study of development but rather a study of the child at a given
age (McCall, 1977). Meta-analysis can be used to combine stud-
all available evidence, (b) identification of robust findings, and
(c) the ability to determine whether age interacts with other
variables of interest (e.g., methodological moderators). However, meta-analysis does not permit the same degree of causal
ies of subjects at different ages, as in a cross-sectional study.
Second, we examined whether there are age-related differences
inference found in longitudinal studies (Cronbach. 1984). Specifically, differences among age groups can result from either age
in twin similarity. On the basis of recent behavior genetics theory and data (McCall, 1983; Plomin & Daniels, 1987; Rowe &
Plomin, 1981), we predict that as twins grow up, they grow
effects or cohort effects, the latter of which is only interesting
apart; that is, twin similarity should decline with age. The importance of the nonshared environment is presumed to increase over time, as children's experiences move outside the
nesses.
family.
Researchers have begun to realize that meta-analysis can be
used to summarize a body of research through the computation
have traditionally studied twins to compute heritability coeffi-
from a historical perspective. Thus, like most methodologies,
developmental meta-analysis has both strengths and weakTwin studies are based on a philosophy and methodology that
make them perfect candidates for meta-analysis. Researchers
cients. The basic procedure is the same in all twin studies: First,
a sample of twins is obtained. Second, the zygosity of the twin
pairs is determined (i.e., monozygotic, or MZ, twins share
of effect-size estimates. However, most researchers may be unaware that specific hypotheses can be tested by performing con-
100% of their genes and dizygotic, or DZ, twins share, on aver-
trast analyses on the effect sizes of independent studies (Rosenthai, 1984). A developmental meta-analysis is thus denned as a
age, 50% of their genes). Third, individual difference measures
are administered to all twins. Fourth, an intraclass correlation
between twins is computed, once for the MZ twins and once for
meta-analysis with age contrasts.
The advantages of being able to perform age contrasts within
the DZ twins. The expectation is that if a given trait or ability
has a genetic component, then the intraclass correlation will be
higher for the MZ twins than for the DZ twins.
This research was supported by grants from the Harvard Graduate
Society and by National Institute of Mental Health Grant MH41807
awarded to Kathleen McCartney, who also acknowledges the support
of the Whitcomb family.
We would like to thank Robert Rosenthal for frequent statistical consultations and Maura Kerrigan for her help in coding articles. We would
also like to thank the reviewers, David Buss, Elizabeth Jordan, Carolyn
Mebert, Edward J. O'Brien, Sandra Scarr, Deborah Vandell, members
of Murray Straus's research seminar, and especially Victor Benassi for
their comments on an earlier draft of this article. This article was presented by Kathleen McCartney at the International Conference on Psychology in Sydney, Australia, August 1988.
Correspondence concerning this article should be addressed to Kathleen McCartney, Department of Psychology, Conant Hall, University of
New Hampshire, Durham, New Hampshire 03824.
Consequently, every twin study contains the data for, and ideally should report, the MZ and DZ intraclass correlations.
These correlations can easily be used in a number of meta-analytic procedures, including age contrasts; however, this has not
been done. Typically, the twin method has been used to estimate
components of variance for genetic and environmental influence. The assumptions of the method continue to be questioned
(Goldsmith, 1983; Hoffman, 1985). The most critical assumption is that the degree of environmental similarity is the same
for MZ and DZ twins. If MZ twins, because they look alike,
experience more similar environments than DZ twins, then
heritability computations would also reflect this environmental
similarity (Plornin, DeFries, & McClearn, 1980).
226
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227
GROWING UP AND GROWING APART
However, twin studies are useful for purposes other than the
estimation of heritability. Twin studies are actually within-family studies, in that more than one member of a family is studied.
Table 1
Categorization of Identified Studies From Literature
Search (Based on Abstracts)
Longitudinal, within-family studies are needed to assess the relCategory
n
Codable
Uncodable
Anecdotal or case studies
Theoretical
No relevant data
Foreign language
Biological
Animal
Predated
Dissertations
Miscellaneous
130'
17
120
81
114
83
141
9
9
52
25
16
11
15
11
18
1
1
7
3
Total
764
100
ative importance of shared and nonshared experiences of siblings.
Several longitudinal, within-family studies do, in fact, suggest
that the older siblings become, the less like one another they
appear on various indexes of intelligence and personality. For
example, three adoption studies have shown that adopted siblings, who are genetically unrelated, look moderately similar on
intelligence tests and personality inventories in early childhood
but do not resemble one another at all by later adolescence,
presumably because the effect of the shared environment wanes
(Kent, 1985; Loehlin, Willerman, & Horn, 1987;Scarr&Weinberg, 1978). The Louisville twin study (Wilson, 1983) showed
that DZ twins became less similar over time on IQ. However,
MZ twins became more similar over time, perhaps because they
seek and are exposed to highly similar environments.
In addition, a preliminary report of the Minnesota study of
twins reared apart and together showed that the common family
environment accounted for little variance on 12 of 14 personality scales (Tellegen, Lykken, Bouchard, Wilcox, Segal, & Rich,
1988). Because the "environment," broadly calculated, did account for substantial variance, one possibility is that nonshared
experiences play a prominent role in development.
These findings were at first surprising to developmentalists,
who have traditionally focused on the role of the shared family
environment in psychological development, as reflected in traditional socialization theory (see Maccoby & Martin, 1983).
This perspective assumes that influential environmental experiences are shared by siblings, because they take place within the
family (e.g., parental discipline, attitudes, and values). The prediction that follows from this perspective is that the longer siblings live together, the more like one another they should become.
A developmental meta-analysis of twin studies allows the
comparison of predictions concerning the importance of the
shared and nonshared environments of siblings over time.
Methodological moderators, especially those that might be associated with age—for example, method of report (self vs. parent)—are also considered in an effort to rule out alternative
hypotheses.
Method
Literature Search
We conducted a computerized literature search of Psychological Abstracts, using twins, heterozygotic twins, and monozygotic twins as descriptors. The time span covered January 1967 through December
1985. This procedure yielded 749 studies; an additional 15 studies were
discovered through secondary sources, for a total of 764 studies.
The abstracts of all 764 studies were classified as codable or uncodable. Codable studies were defined as those from journals that included
intraclass re for MZ twins, DZ twins, or both kinds of twins on personality or intelligence variables. Uncodable studies were subdivided into
nine categories: (a) anecdotal or case studies, which were excluded because no r was possible; (b) theoretical papers, which were excluded
because they presented no new data; (c) no-relevant-data studies, which
• Of these 130 papers, 103 were actually used in the meta-analysis. The
remaining 27 papers did not contain data that contained intraclass rs
or that could be converted to intraclass rs. These 27 papers were receded
to the no-relevant-data category after the papers were read.
were excluded because intraclass rs were not included and could not be
calculated; (d) foreign language papers; (e) studies on psychopathology
or biology, which were excluded because the dependent variables were
not in the targeted areas of personality and intelligence; (f) animal studies; (g) predated studies, which were excluded because an updated study
with more data was available; (h) dissertations, which were excluded
because many were duplicated in later journal articles; and (i) miscellaneous studies that included articles we could not locate through interlibrary loan, papers from various conferences and proceedings, and papere by Sir Cyril Burt, which have been shown to contain fraudulent
data (Heamshaw, 1979). It should also be noted that unrefereed books
and book chapters were excluded by the computer literature search procedure. Thus, this search was limited to journal articles on the similarity of twins' personality and intelligence. Table 1 displays the number
and percentage of studies per category. Note that 130 twin studies were
read for this meta-analysis. Of these 130 papers, 103 actually contained
intraclass re or data that could be converted to intraclass re; these 103
papers were used in the meta-analysis (see the appendix for references
for the studies).
Because the validity of all meta-analyses rests on the extent to which
literature searches are both comprehensive and representative, we
searched more broadly than was necessary. We believe that the comprehensiveness of the search was guaranteed by the broad descriptor terms
used in the computer search. Certainly the search identified studies on
a wide range of topics, from a wide range of periodicals. Although only
13.4% of studies from the literature search were coded, it is important
to consider that all the studies excluded, with the exception of dissertations, were those that did not present relevant data on personality or
intelligence.
Even if the search were not comprehensive, it would only be a problem if the identified studies were not representative of studies published,
and there is no reason to suspect any bias. Some literatures—for example, that on sex differences—are biased with respect to which studies
are published (see Hall, 1987). This is referred to as the "file drawer"
problem (Rosenthal, 1984), because unpublished, relevant studies can
only be located in the file drawers of researchers. However twin studies
are unlikely to be found in file drawers because twins have been considered to be valuable subjects. In fact, even case studies are likely to be
published (16% of studies identified in this computer search were case
studies). More important, the file drawer problem is not an issue here,
because this is a study of a moderator, namely age.
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K.. MCCARTNEY, M. HARRIS, AND F. BERNIERI
228
ences between the two selection strategies, so we report the data
Coding the Studies
for all studies in order to simplify our presentation.
Three coders each read approximately one third of the studies and
extracted intraclass re separately for MZ and DZ twins for each relevant
dependent variable. Coders recorded the number of male pairs, the
number of female pairs, and the number of mixed pairs (for DZ twins).
Three moderator variables were recorded: age per group, method of
zygosity determination (blood grouping vs. other), and type of report
(self vs. parent). We had planned to use type of DZ twin (same sex
vs. opposite sex) as an additional moderator; however, only 12 studies
included opposite-sex DZ twins (9 of the 12 studies contained data on
twin similarity for intelligence). We decided to include data from DZ
twins that included mixed-sex pairs rather than lose these data; this may
have resulted in a lower DZ intraclass correlation for some traits, although sex differences are far less likely for intelligence than for personality variables. Because the mixed-sex DZ data were from studies of
seven different dependent variables (see categories described in the following section), we did not view this potential bias as a serious problem.
Also, there is no reason to expect that mixed-sex DZ data should affect
the moderator analyses for age.
ated accordingly, where .10 is low, .30 is moderate, and .50 is
large (Cohen, 1977).
Classification of the Dependent Variables
similar to two other reviews that reported median intraclass rs.
Nichols (1978) reported a median intraclass r for general intelligence of .82 for MZ twins (vs. .81 in this study) and .59 for DZ
twins (also .59 in this study). Nichols's review was based on the
Dependent variables were classified via group consensus based on the
knowledge of the researchers and on descriptions by authors. Intelligence was subdivided into five categories: verbal intelligence, quantitative intelligence, performance intelligence, perception, and total IQ.
Personality-temperament was subdivided into eight categories: activity-impulsivity,1 aggression, anxiety, dominance, emotionality, masculinity-femininity, sociability, and task orientation.
Several personality constructs were not analyzed because they were
examined in fewer than five studies. Thus, we lost constructs such as
creativity, altruism, religiosity, hypnotic susceptibility, and humor. We
excluded one additional category, attachment, because it was measured
very differently across studies (e.g., approach to stranger, approach to
mother, crying, and so on).
Researchers often assessed a single construct with multiple measures
(e.g., self-report and behavioral observation). In such cases, we computed a combined effect-size estimate using the Fisher's z, transformation (Rosenthal, 1984, p. 27). This is preferable to including all effect
sizes from a given study separately, a procedure that would violate the
independence assumption that is essential for many meta-analytic procedures.
Results
Note that there is no agreed-on test of significance to determine whether these rs are reliably different from zero, because
it is not clear whether the degrees of freedom should reflect the
number of studies, which would be conservative, or the number
of subjects across studies, which would be liberal given that observations within studies are not independent. The rs in Table
2 should, therefore, be treated as effect-size estimates and evalu-
Table 2 reveals three important findings. First, the MZ rs are
greater than the DZ rs by .22 for the combined intelligence variables and by .29 for the combined personality variables. Although a combined personality variable may not be readily interpretable, especially if traits are differentially heritable,2 the
data for a combined personality variable are presented here for
comparison purposes. Consider that these estimates are quite
literature through 1971, whereas this meta-analysis covers the
years 1967 through 1985. Only nine studies in the present metaanalysis came from the 5-year overlap between reviews. This
study thus provides a replication of Nichols's review with the
report of nearly identical estimates of intellectual concordance
for MZ and DZ twins. The median intraclass rs for intelligence
reported by Bouchard and McGue (1981), which covered the
literature through 1980, are comparable: .85 for MZ twins and
.58 for DZ twins. For personality, this study also reported intraclass rs similar to those of Nichols (1978): .48 for MZ twins
(vs. .51 in the present study) and .29 for DZ twins (vs. .22 in
the present study). Although the primary purpose of this study
was to conduct a developmental analysis, the value of obtaining
up-to-date and accurate effect-size estimates cannot be overlooked.
A second interesting feature of Table 2 is the low variance
among the rs within the category of intelligence and within the
category of personality. That this is true for the personality
scales is especially intriguing. Researchers have recently hypothesized a genetic role in certain personality variables, most
notably sociability (A. Buss & Plomin, 1984) and behavioral
Mean Effect-Size
Estimates
inhibition (Kagan, Reznick, & Snidman, 1988). Variables such
Table 2 presents mean intraclass rs separately for MZ and
as masculinity-femininity and task orientation have typically
been considered as having strong socialization components.
DZ twins per dependent variable. Mean rs were calculated using
two methods: (a) giving each study unit weight, that is, the simple mean effect size across all studies, and (b) weighting the in-
The homogeneity of the intraclass rs for the personality variables included here, however, suggests that the various facets of
personality are not differentially affected by genetic or environ-
traclass r for each study by the number of twin pairs for that
mental influences.
study. Because there was little difference between the results obtained by using these two weighting strategies, we limit ourselves to a discussion of the data obtained by using unit weighting. In both cases, means were computed following a Fisher's z,
transformation. Analyses were computed twice: first for all of
the data, which included nonindependent intraclass rs from
longitudinal and cross-sectional studies; and second for strictly
independent intraclass rs, excluding those from longitudinal
and cross-sectional studies. There were no important differ-
1
Although these two constructs no doubt seem distinct to some readers, measures of activity and impulsivity were sometimes combined in
research reports and are therefore combined here.
2
Rose (1988) found evidence for differential heritability of personality traits on the Minnesota Multiphasic Personality Inventory; however,
Loehlin and Nichols (1976) concluded that there is little evidence for
differential heritability of personality on the California Psychological
Inventory.
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229
GROWING UP AND GROWING APART
Table 2
Mean Inlradass rs for Monozygotic (MZ) andDizygotic (DZ)
have been included, on the basis of some random selection pro-
Twins From All Studies Coded
about practice effects. Alternatively, we could have included the
Weighted
by study
Variable type
and variables
Intelligence
Verbal
Quantitative
Performance
Perception
Total IQ
Number
of studies
a
29
8
29"
I)
42"
M»
MZ
DZ
Weighted
by sample
MZ
DZ
cedure, we decided not to do so because we were concerned
youngest age group, but this procedure would have introduced
an age bias. This decision to include only independent studies
does not constitute any bias and is not consequential in that the
ratio of nonindependent studies to independent studies was low.
Table 3 presents the correlations between age and effect sizes
for all intelligence and personality variables, computed sepa-
.76
.71
.71
.55
.81
.47
.51
.47
.45
.59
.76
.74
.70
.55
.81
.48
.57
.47
.42
.61
dian of mean ages across studies varied somewhat. The correlations of effect size and age for the intelligence variables show
.72
.50
.72
.51
that DZ twins become more dissimilar over time than MZ
rately for MZ and DZ twins. Note that the age ranges for all
variables covered at least the period from 7 to 20 years; the me-
twins; however, this difference is in large part accounted for by
Personality
Activity-impulsivity
Aggression
Anxiety
Dominance
Emotionality
Masculinity-femininity
Sociability
Task orientation
the analysis of quantitative intelligence. The correlations of
31"
8
9
7
18'
9
33'
7
M*
" DZ results are based on I fewer studies.
lated on Fisher's z-transformed rs.
.58
.49
.59
.50
.54
.50
.50
.42
.22
.28
.18
.25
.19
.33
.16
.17
.51
.49
.54
.51
.51
.44
.20
.29
.19
.21
.15
.36
.19
.19
.51
.22
.50
.22
b
.47
.52
Arithmetic mean calcu-
effect size and age for personality variables are quite similar for
MZ and DZ twins.
The overall pattern of correlations in Table 3 is consistently
negative, which indicates that as twins get older they become
less similar. Again, as with Table 2, there is no generally accepted test of significance for these rs. They should be interpreted as effect-size estimates.
An alternative way to examine the effect of a moderator is
through contrast analysis. Contrast analysis offers the advantage
of providing a significance test. To determine whether age was
a moderator of similarity, age contrasts were computed separately for MZ and DZ twins within the categories of intelligence
and personality, following the procedure outlined by Rosenthal
Third, the rs for intelligence are consistently greater than the
rs for personality. This difference may suggest that intelligence
is less susceptible to environmental influences than is personality. An alternative explanation is that because personality measures are typically more unreliable than intelligence measures,
Table 3
Correlations Between Intraclass rs and Age of Twins
(From Independent Studies)
the personality correlations are therefore lower.
r
Variable type
and variables
Age as a Moderator
The most straightforward way to examine the effect of a moderator within a meta-analysis is to correlate the moderator, in
this case mean age, with the effect size per study. It should be
noted that the midpoint of the age range had to be used as the
best estimate of the mean age when it was not reported. Because
age ranges were sometimes large, this had the effect of lowering
the power of this analysis, thus making it relatively conservative.
Intelligence
Verbal
Quantitative
Performance
Perception
Total IQ
M
Number
of studies
22
8
14
5
16*
b
Age
DZ Median
MZ
range
twins twins
age
in years
-.14
-.13
-.25
-.64
.10
.15
-.82
-.36
-.79
-.25
-.22
-.50
-.48
-.09
-.34
-.33
-.06
-.49
.67
.07
10.0
10.5
10
7.7
7.8
2-84
6-41
6^tl
6-20
1-59
The analyses were done twice: once using raw mean age in years
and once using transformed age in order to minimize points of
high leverage, such that 23 years was the maximum score possible (i.e., any age greater than 23, e.g., 40, was coded as 23).
Because the results were nearly identical for the two sets of analyses, only the correlations between intraclass rs and untransformed age are reported.
Only independent studies (i.e., no longitudinal or cross-sectional studies) were used in the examination of moderator variables. This is also a conservative procedure in that some data
points were excluded. However, this procedure does not violate
the independence assumption and avoids biasing results that
would occur by heavily weighting a subset of longitudinal studies. Also, although data from one age group per study could
Personality
Activity-impulsivity
Aggression
Anxiety
Dominance
Emotionality
Masculinity-femininity
Sociability
Task orientation
M"
14'
8
5
5
8"
7
20°
5
-.11
-.81*
-.24
-.69
-.30
.30
-.74
.26
-.89
7.6
11.5
20.4
30.0
6.3
16
16.5
28
1-50
7-49
7-30
7-50
1-50
7-50
3-50
1-50
-.32
Note. MZ = monozygotic; DZ = dizygotic.
a
DZ results are based on 1 fewer study. b Arithmetic mean calculated
on Fisher's z-transformed rs.
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K. MCCARTNEY, M. HARRIS, AND F. BERNIERI
230
To summarize the results of these two analyses, both demon-
Table 4
strate a general negative association between twin similarity
and age. Both analyses also demonstrate variability in patterns
across variables. For example, there is a strong association be-
Contrasts of the Effects of Twins'Age on Intraclass rs
(From Independent Studies)
Age contrast Z
Variable type
and variables
Intelligence
Verbal
Quantitative
Performance
Perception
Total IQ
tween twin similarity and age for activity-impulsivity and for
Number
of studies
MZ twins
DZ twins
masculinity-femininity, whereas there is little association between similarity and age for aggression and for emotionality.
22
8
14
5
16"
-0.58
-0.42
-2.07**
-0.89
1.00
0.29
-2.28"
-0.90
-0.87
-1.04
Methodological Moderators
-0.09
-0.40
Meta-analysis has been criticized by some who believe that
all studies should not be treated "equally." This is sometimes
referred to as the "apples and oranges" problem, following the
adage that one cannot add apples and oranges. Wachter (1988)
described this concern best: "Meta-analysis accommodates it-
Personality
Activity-impulsivity
Aggression
Anxiety
Dominance
Emotionality
Masculinity- femininity
Sociability
Task orientation
14'
8
5
5
8'
7
20'
5
M*
-4.79***
0.05
-1.91*
2.44**
-0.56
-2.95**
-1.42
-1.75*
-3.53***
-0.39
0.38
0.15
0.84
-1.76*
0.83
-0.58
-0.34
-0.39
Note. MZ = monozygotic; DZ = dizygotic.
" DZ results are based on 1 fewer study. " Arithmetic mean calculated
on Fisher's z-transformed rs.
*p<.W. **p<.05. ***/)<.01.
and Rubin (1982). To create contrast weights, we simply subtracted the mean age of studies from the mean age per study,
such that the weights summed to zero.
The results of the age contrasts are displayed in Table 4. We
report significant contrasts at p < .10 because each study is
self to a world in which bad science drives out good by weight
of numbers" (p. 1407). The answer to this criticism is that
methodological variables suspected of compromising the science, or variables suspected of altering the size of a relation, can
be examined by contrast analysis or by correlational analysis.
There may be other variables that should be considered here.
For example, method of zygosity determination might compromise the results of a twin study. In addition, some variables
might moderate the relation between age and twin similarity,
for example, type of report (self vs. parent) and age differences
in reliability of assessment. These three moderators are considered in the following paragraphs for three dependent variables:
total IQ, sociability, and activity-impulsivity. Total IQ was selected because it is the most robust measure of intelligence. Sociability and activity-impulsivity were selected because they are
based on the largest number of studies in the personality domain. In addition, these two variables provide an interesting
contrast in this context because there are age effects for one,
activity-impulsivity, but not for the other.
based on many observations, which increases confidence in the
Type of report. The vast majority of personality constructs
estimate. There was a general pattern of negative Zs, indicating
that re decreased with age. Seventeen of 26 Zs were negative and
8 of the 9 significant Zs were negative. A negative Z means that
there is decreasing concordance between twins as they get older.
The age contrast was significant for both MZ and DZ twins
were measured by self-report. In 13 studies, personality was assessed by parent report. Twelve of these studies concerned temperament and 1 concerned sex roles. In 4 of the 12 studies, behavioral observations were collected in addition to parent re-
on two personality variables: activity-impulsivity and masculinity-femininity. In addition, the age contrast on MZ twins was
some measures of personality. If parents of MZ twins are prone
to view their children as more similar (see Jones, 1955; Koch,
significant for three other personality variables: anxiety, dominance, and task orientation. The contrast on dominance, however, was positive, indicating increasing similarity for MZ twins
1966), then the association between age and report method
would be a confound. However, several studies have documented a lack of bias between parents' reports on their twins
over time.3 For intelligence, there was one significant age con-
and zygosity. Ratings of confusability of twins are not signifi-
trast for MZ twins, on performance, and one significant age
contrast for DZ twins, on quantitative intelligence.
Any differences between the contrast and correlational analy-
cantly correlated with difference scores on four temperament
traits (Plomin, Willerman, & Loehlin, 1976). Moreover, moth-
ses are probably the result of points of high leverage in the computation of the Pearson rs; the number of independent studies
per category is relatively small despite the fact that we began
with a data base of 103 studies. Although some prefer contrast
analysis, because it yields a significance test and because studies
are weighted by number of subjects, there are advantages to the
correlational procedure. The r between a moderator and effect
sizes is itself an effect size. There is no straightforward way to
compute an effect-size estimate from a contrast analysis within
meta-analysis, because n is ambiguous.
port. There is an association between age and report method for
ers who have misdiagnosed their twins' zygosity report neither
greater nor smaller differences in behavioral similarity (Scarr,
1968).
3
We plotted the relation between intraclass r and average age of sample separately for MZ and DZ twins for each dependent variable. Inspection of the data revealed that a single point of high leverage was
responsible for the positive Z on dominance; the youngest subjects generated the lowest intraclass rs on dominance in a unique behavioral ratings task. Inspection of other plots yielded no other points of noticeably
high leverage.
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GROWING UP AND GROWING APART
Nevertheless, method of report remains controversial in twin
studies (Bates, 1980). For this reason, we dummy-coded
method of report (self vs. parent) and correlated it with MZ re
and DZ re for sociability and activity-impulsivity (intelligence
was never assessed via parent report).
For sociability, the correlation between method of report and
twin similarity was large and negative for the MZ twins (r =
—.55, p < .05), but large and positive for DZ twins (r = .48, p <
.05). This pattern shows that parent reports are more similar
than self-reports for MZ twins and are less similar than selfreports for DZ twins.
For activity-impulsivity, the pattern of results was somewhat
different. The correlation between method of report and twin
similarity was large and negative for both MZ twins (r = —.75,
p < .01) and DZ twins (r = -.42, p > .20). For both types of
twins, intraclass rs were greater for parent reports than for selfreports. It is probable that parent reports are less valid than selfreports, because parents make two sets of ratings.
For this reason, correlations between intraclass rs and age
were computed again without data from parent reports. For activity-impulsivity there was actually a somewhat stronger age
effect (see Table 3). For the eight self-report studies of MZ twins,
the correlation between age and twin similarity was —.51; for
the seven self-report studies of DZ twins, the corresponding correlation was —.42. Thus, even with self-report data only, there
is decreasing twin similarity on activity-impulsivity with age.
For sociability, there was again little association between twin
similarity and age for the self-report studies. For the 14 selfreport studies, the correlation between age and twin similarity
for both MZ and DZ twins was -.02.
Age and reliability of measures. The reliability of measures
changes with age. Intelligence tests become more reliable with
age, with the greatest change occurring between the preschool
and early grade-school years (Anastasi, 1982). For personality,
however, this change is less clear. For example, test-retest correlations for the California Psychological Inventory (CPI; Gough,
1975), the most commonly used scale for adults in this set of
studies, are comparable to those of the Emotionality, Activity,
and Sociability Scale (EAS; A. Buss & Plomin, 1984), the most
commonly used scale for children in these studies. For sociability, however, reliability is lower on the EAS for 3-year-olds (.58)
than on the CPI for young adults (.68 for boys and .71 for girls).
For this developmental meta-analysis, increasing measurement reliability works against the hypothesis that there is decreasing similarity over time. For this reason, the correlation
between age and twin similarity was examined in only those
studies for which the mean age of subjects was 5 years or more.
(Of course, this restricts the range of ages considered, which
may in itself affect the analyses.) The results were quite similar
to those reported in Table 3. For total IQ, the r for MZ twins
was .28; for DZ twins it was -.36. For sociability, the r for MZ
twins was -.16; for DZ twins it was .00. For activity-impulsivity, the r for MZ twins was - .42; for DZ twins it was - .27. Thus,
age differences in assessment reliabilities do not appear to have
confounded the results of this developmental meta-analysis.
A related problem for developmentalists is that the operationalization of constructs changes over time. For example, intelligence for a 2-year-old is tested by tasks such as bead stringing;
for 16-year-olds it is tested by tasks such as mazes and block
231
design. Similarly, sociable behaviors of 2-year-olds and 16-yearolds also differ. Differences in the operationalization and reliability of assessment tools for subjects of different ages are unsolved problems for developmentalists who study constancy
and change in human development (Kagan, 1980). It is for this
reason that the statistical issues in the assessment of change have
received great attention (Cronbach & Furby, 1970; Judd &
Kenny, 1981; Richards, 1976).
Zygosity determination as a moderator. Blood grouping is
the most reliable method of zygosity determination. When 20
genetic markers are analyzed in blood samples, accuracy approaches 100% (Plomin et al., 1980). Less reliable methods include ratings of picture similarity, comparison of fingerprints,
and simply asking twins whether they are identical twins.
Zygosity was dummy-coded to reflect blood grouping versus
other methods. We expected higher intraclass rs for MZ twins
and lower intraclass rs for DZ twins in studies using blood
grouping, because this method would tend to purify the MZ
and DZ samples. Because there was no reason to expect differences in the zygosity moderator to be associated with specific
traits, we performed contrasts on mean intelligence and mean
personality.
For mean personality, as predicted, there was a trend for MZ
twins to generate higher intraclass rs in studies using blood
grouping (contrast Z = 1.83, p < .10); for DZ twins, however,
method of zygosity determination did not moderate effect sizes
(Z = .38). Similarly, for intelligence, zygosity determination did
not moderate the effect sizes of either MZ (Z = -.83) or DZ
(Z = .24) twins.
From the present set of analyses, there is no strong evidence
to suggest the methodological superiority of blood grouping
with respect to the prediction of intraclass rs. The cruder methods of zygosity determination, which are highly correlated with
blood grouping, perform well.
Components of Variance Analyses
As previously discussed, the computation of components of
variance from twin data is controversial. Criticism has focused
on heritability (if). In twin studies, h2 is computed by doubling
the difference between MZ and DZ intraclass rs (see Plomin,
1986, p. 15). A statistical concern with h2 is the relative unreliability of difference scores. The standard error of differences
between correlations is larger than the standard error of a simple correlation. In addition, there are conceptual problems associated with the computation of A2. Scarr and Kidd (1983)
have outlined three main limitations with the concept of h2:
First, r? depends on the range of environmental variation (and
it is difficult to assess whether samples are indicative of populations for many psychological traits); second, A2 requires quantitative definition of a trait (this is less of a problem with metaanalysis, where an estimate would be across measures); third,
r? estimates assume the genetic and environmental components
are additive and not correlated. This final point has been disputed in recent theoretical work (D. Buss, 1987; Plomin, DeFries, & Loehlin, 1977; Scarr & McCartney, 1983)and in recent
empirical work (Pederson, Plomin, McClearn, & Friberg,
1988).
Environmental components of variance can also be esti-
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K. MCCARTNEY, M. HARRIS, AND F. BERNIERI
232
of cross-sectional study. The major advantage may be that an
entire body of literature can be brought to bear on a develop-
Table 5
Correlations Between Components of Variance
mental issue. For this reason, developmental meta-analyses can
be particularly useful in orienting the focus of future longitudi-
and Age of Twins
Amount of data
Heritability
Shared
environment
Nonshared
environment
All data
Intelligence
Sociability
Activity-impulsivity
.36
-.46
.03
-.37
.40
-.21
-.15
.33
.48
nal research. Interpretation of a developmental meta-analysis is
not straightforward. Essentially, age is a correlate of effect-size
estimates. Because age cannot be experimentally manipulated,
other variables that might moderate the association between age
and effect-size estimate must be considered. It is through additional moderator analyses that alternative hypotheses to those
associated with age can be considered. Here, two such moderators were considered: type of report and reliability of assess-
Excluding data where
mean age is 5
years or less
ment. As with all meta-analyses, variables associated with the
Intelligence
Sociability
Activity-impulsivity
Excluding parent report data
Sociability
Activity-impulsivity
.52
-.18
-.29
-.50
.11
.05
-.28
.16
.42
soundness of the methodology should be considered, so that
good studies are not outweighed by bad ones. Here, one such
.08
.09
-.12
-.39
.02
.60
changes in twin similarity over time. Recent theory (e.g.,
Plomin & Daniels, 1987) and a handful of longitudinal adoption
studies suggest that the importance of the nonshared environ-
Nate. The monozygotic twin age weight was used in these reported analyses. Corresponding analyses with the dizygotic twin age weight were
nearly identical.
moderator was considered: method of zygosity determination.
The substantive purpose of this article has been to examine
ment increases with age. We were able to assess the relative importance of the shared and nonshared environments by reconceptualizing twin studies as within-family studies and by deter-
mated from twin data, and these components have the same
limitations associated with them as h2. In addition, critics have
questioned the validity of indirect assessments of the environment (Wachs, 1983). For example, the shared environmental
2
2
mining that age contrasts in a meta-analysis could be used to
test a developmental hypothesis. The results of this meta-analysis demonstrate a developmental trend: To some extent and for
some variables, as twins grow up, they grow apart; that is, twin
similarity decreases with age.
This pattern was more true for some variables than for others.
In both the correlational analysis and the contrast analysis, cer-
effect (es ) is estimated by MZ, — h ; the nonshared environmental effects (ens2) are estimated by 1 — MZ, (Plomin, 1986,
p. 69). These two environmental effects and h2 sum to 1. Again,
it is important to remember that an additive model is probably
simplistic.
tain domains of personality—for example, activity-impulsivity
and masculinity-femininity—showed substantial change over
time. Other domains, such as anxiety and task orientation,
To determine the source of decreasing twin similarity, age
showed similar changes for MZ twins only. There was less agree-
was correlated with these three components of variance for intelligence, sociability, and activity-impulsivity (see Table 5).
ment between the correlational analysis and the contrast analysis for intelligence than for personality. The correlations between mean age and effect size of study were comparable to
These analyses were computed three ways: (a) with all data, (b)
with only those data in which the mean age of subjects was 5
years or more, and (c) excluding parent report data. These analyses must be viewed with caution because of the limitations,
outlined earlier, associated with components of variance analyses. In addition, it is not clear how reliable these analyses are,
those in the personality realm; however, the contrast Zs were
small. The correlational analysis showed greater dissimilarity
over time for DZ twins on overall intelligence. This pattern is
in contrast to the findings for some indexes of personality.
There were some moderators of effects. For example, parent
especially when they are based on so few data points. These
reports appear to bias ratings of temperament. Another moder-
analyses are presented primarily for heuristic purposes.
For intelligence, h2 increased over time, more so when the less
reliable preschool data were excluded. Conversely, es2, and to a
ator, sex, should be considered in future work, in light of Rose's
(1988) finding of a Gender X Age interaction on 4 of 9 personality variables. Other moderators studied here, such as age differ-
lesser extent ens2, decreased over time. For sociability, the results changed when either the preschool data or the parent re-
ences in reliability and method of zygosity determination, ap-
port data were excluded. In these cases, there was little evidence
for change of any sort. For activity-impulsivity, ens2 increased
peared to have little, if any, effect. However, power in most analyses was low. Although 103 studies were coded in this
investigation, more than half of the 13 variables were assessed
over time and es2 decreased over time, especially for the analyses of self-report data.
in fewer than 20 studies. This limitation weakens somewhat the
Discussion
This robustness was demonstrated by the consistency between the average effect-size estimates reported here and the
The methodological purpose of this article has been to demonstrate the utility of developmental meta-analysis, where age
is used as a moderator of effect-size estimates. Developmental
meta-analysis shares many of the advantages and disadvantages
robustness of the findings. Nevertheless, it must be remembered
that each data point is based on multiple subjects in a study.
median rs reported by Bouchard and McGue (1981) for intelligence and by Nichols (1978) for personality and intelligence.
Nichols's observation about the similarity between the two
kinds of twins across traits is relevant. His data and our data
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233
GROWING UP AND GROWING APART
show that "a twin study is likely to find a difference between
identical and fraternal correlations of about .20 regardless of
the domain or the trait that is being investigated!" (Nichols,
1978, p. 163). For this reason, we believe that in the future,
singular studies of twins conducted for the sole purpose of obtaining heritability estimates on specific psychological indexes
are unlikely to make any significant contribution.
Certainly, most twin and adoption studies show that the environment accounts for a substantial portion of variance (Loehlin, Willerman, and Horn, 1988). Our purpose here has not
been to compute components of variance. However, age was
correlated with components of variance in order to examine
developmental patterns. Two speculations can be made based
on these exploratory analyses. First, heritability seems to increase over time for IQ. This may reflect an age-related increase
in MZ similarity and the age-related decrease in DZ similarity.
This pattern was found in the longitudinal Louisville twin study
(Wilson, 1983); however, we found it for total IQ only. Second,
for IQ and activity-impulsivity the importance of the shared
environment decreased over time; the nonshared environment
increased over time for activity-impulsivity. It was difficult to
analyze age-related change in components of variance with respect to sociability, because the pattern changed when the parent report data were eliminated.
Thus, the results of this developmental meta-analysis of twin
studies support recent developmental theory and recent family
research in that they demonstrate the importance of nonshared
experiences generally (e.g., Plomin & Daniels, 1987). This is
especially impressive in this context: Twin studies probably
overestimate the importance of the shared environment, because twins no doubt experience more similar environments
than do other siblings (Plomin, 1986). In other words, this pattern may be greater for nontwin siblings.
Patterns associated with nonshared environmental effects
may be complicated by the fact that there are probably two distinct types. The nonshared environment consists of both nonsystematic experiences (stochastic events) and systematic experiences. It may be that nonsystematic experiences lead to
differences and systematic experiences increase similarity when
genetic predispositions are shared.
There are some data on differential parental treatment to
support this thesis. Lytton's (1977) observations of parentchild interaction with both MZ and DZ twins suggest that parems respond to differences between the twins based on actual
rather than perceived zygosity. Dunn, Plomin, and Nettles
(1985) found greater differences in maternal affection between
adopted siblings, who are not genetically related, than between
biological siblings.
Yet if people make their own environments through probabilistic associations with genetic predispositions, as Scarr and McCartney (1983) have suggested, then one might expect that MZ
twins would become less dissimilar over time than DZ twins,
because MZ twins would be expected to create similar niches
in life. The results of this meta-analysis are mixed on this issue.
Although the correlational analysis shows that DZ twins become more dissimilar over time on intelligence, the contrast
analysis shows little evidence for change, in one direction or the
other, for either MZ or DZ twins. For personality, the correlational analysis reveals a similar pattern of dissimilarity over
time for both MZ and DZ twins, although the contrast analysis
shows many more significant effects for MZ twins.
An ad hoc explanation for why MZ twins would become
more dissimilar over time than DZ twins is the greater need of
MZ twins to appear different. Schachter (1982) introduced the
term sibling deidentification to describe a process through
which family members might define siblings as different or contrasting. Schachter and Stone (1985) found evidence for deidentification among same-sex siblings and among first-sibling pairs.
Perhaps this happens because these children are more likely to
be compared with one another. Similarly, MZ twins, who are
the most likely of all sibling pairs to be compared with one another, may be more likely to deidentify than DZ twins, at least
on some measures of personality.
Thus, because there is little evidence that DZ twins become
more dissimilar over time than MZ twins, it appears that nonsystematic environmental effects might play a more dominant
role than systematic environmental effects. The implications of
this conclusion for future research are challenging. One approach might be to target certain environmental effects that
would seem to be unrelated to genetic predispositions or shared
family experience, for example, being randomly placed in a
classroom with a particularly skilled teacher or being hospitalized because of injury.
A challenge also lies in the nearly certain fact that many developmental processes operate simultaneously. For example,
the shared and nonshared environments each affect development, to some extent. In addition, siblings may both identify
and deidentify, to some extent. Moreover, these processes may
interact differently for different traits and abilities during
different developmental periods. As we search for the methods
to study multiple developmental processes, developmental
meta-analysis will have increasing utility.
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Received July 28, 1988
Revision received May 29, 1989
Accepted June 16,1989 •