Psychological Bulletin1990. Vol. 107, No. 2, 226-237
Copyright 1990 by the American Psychological Association, Inc.0033-2909/90/S00.75
Growing Up and Growing Apart: A DevelopmentalMeta-Analysis of Twin Studies
Kathleen McCartneyUniversity of New Hampshire
Monica J. HarrisUniversity of Kentucky
Frank BernieriOregon State University
Developmental change in twin similarity was examined with age contrasts in a meta-analysis of twinstudies 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 indi-cated 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 compo-nents of variance for heritability, the shared environment, and the nonshared environment. Mecha-nisms through which the nonshared environment may operate are discussed.
The purpose of this article is twofold. First, we offer meta-
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-
ies of subjects at different ages, as in a cross-sectional study.
Second, we examined whether there are age-related differences
in twin similarity. On the basis of recent behavior genetics the-
ory and data (McCall, 1983; Plomin & Daniels, 1987; Rowe &
Plomin, 1981), we predict that as twins grow up, they grow
apart; that is, twin similarity should decline with age. The im-
portance of the nonshared environment is presumed to in-
crease over time, as children's experiences move outside the
family.
Researchers have begun to realize that meta-analysis can be
used to summarize a body of research through the computation
of effect-size estimates. However, most researchers may be un-
aware that specific hypotheses can be tested by performing con-
trast analyses on the effect sizes of independent studies (Rosen-
thai, 1984). A developmental meta-analysis is thus denned as a
meta-analysis with age contrasts.
The advantages of being able to perform age contrasts within
This research was supported by grants from the Harvard GraduateSociety and by National Institute of Mental Health Grant MH41807
awarded to Kathleen McCartney, who also acknowledges the supportof the Whitcomb family.
We would like to thank Robert Rosenthal for frequent statistical con-sultations and Maura Kerrigan for her help in coding articles. We wouldalso like to thank the reviewers, David Buss, Elizabeth Jordan, CarolynMebert, Edward J. O'Brien, Sandra Scarr, Deborah Vandell, membersof Murray Straus's research seminar, and especially Victor Benassi fortheir comments on an earlier draft of this article. This article was pre-sented by Kathleen McCartney at the International Conference on Psy-chology in Sydney, Australia, August 1988.
Correspondence concerning this article should be addressed to Kath-leen McCartney, Department of Psychology, Conant Hall, University ofNew Hampshire, Durham, New Hampshire 03824.
meta-analysis include (a) obtaining a combined estimate from
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). How-
ever, meta-analysis does not permit the same degree of causal
inference found in longitudinal studies (Cronbach. 1984). Spe-
cifically, differences among age groups can result from either age
effects or cohort effects, the latter of which is only interesting
from a historical perspective. Thus, like most methodologies,
developmental meta-analysis has both strengths and weak-
nesses.
Twin studies are based on a philosophy and methodology that
make them perfect candidates for meta-analysis. Researchers
have traditionally studied twins to compute heritability coeffi-
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
100% of their genes and dizygotic, or DZ, twins share, on aver-
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
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.
Consequently, every twin study contains the data for, and ide-
ally should report, the MZ and DZ intraclass correlations.
These correlations can easily be used in a number of meta-ana-
lytic 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 influ-
ence. The assumptions of the method continue to be questioned
(Goldsmith, 1983; Hoffman, 1985). The most critical assump-
tion 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
GROWING UP AND GROWING APART 227
However, twin studies are useful for purposes other than the
estimation of heritability. Twin studies are actually within-fam-
ily studies, in that more than one member of a family is studied.
Longitudinal, within-family studies are needed to assess the rel-
ative importance of shared and nonshared experiences of sib-
lings.
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 sib-
lings, 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&Wein-
berg, 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 personal-
ity scales (Tellegen, Lykken, Bouchard, Wilcox, Segal, & Rich,
1988). Because the "environment," broadly calculated, did ac-
count 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 tra-
ditional socialization theory (see Maccoby & Martin, 1983).
This perspective assumes that influential environmental experi-
ences are shared by siblings, because they take place within the
family (e.g., parental discipline, attitudes, and values). The pre-
diction that follows from this perspective is that the longer sib-
lings live together, the more like one another they should be-
come.
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 as-
sociated with age—for example, method of report (self vs. par-
ent)—are also considered in an effort to rule out alternative
hypotheses.
Table 1
Categorization of Identified Studies From Literature
Search (Based on Abstracts)
Category n
Method
Literature Search
We conducted a computerized literature search of Psychological Ab-
stracts, using twins, heterozygotic twins, and monozygotic twins as de-scriptors. The time span covered January 1967 through December1985. This procedure yielded 749 studies; an additional 15 studies werediscovered through secondary sources, for a total of 764 studies.
The abstracts of all 764 studies were classified as codable or uncod-
able. Codable studies were defined as those from journals that includedintraclass re for MZ twins, DZ twins, or both kinds of twins on personal-ity or intelligence variables. Uncodable studies were subdivided intonine categories: (a) anecdotal or case studies, which were excluded be-cause no r was possible; (b) theoretical papers, which were excludedbecause they presented no new data; (c) no-relevant-data studies, which
CodableUncodable
Anecdotal or case studiesTheoreticalNo relevant dataForeign languageBiologicalAnimalPredatedDissertationsMiscellaneous
Total
130'
12081
11483
14199
5225
764
17
1611151118
1173
100
• Of these 130 papers, 103 were actually used in the meta-analysis. Theremaining 27 papers did not contain data that contained intraclass rsor that could be converted to intraclass rs. These 27 papers were recededto the no-relevant-data category after the papers were read.
were excluded because intraclass rs were not included and could not becalculated; (d) foreign language papers; (e) studies on psychopathologyor biology, which were excluded because the dependent variables werenot in the targeted areas of personality and intelligence; (f) animal stud-ies; (g) predated studies, which were excluded because an updated study
with more data was available; (h) dissertations, which were excludedbecause many were duplicated in later journal articles; and (i) miscella-neous studies that included articles we could not locate through interli-brary loan, papers from various conferences and proceedings, and pa-pere by Sir Cyril Burt, which have been shown to contain fraudulentdata (Heamshaw, 1979). It should also be noted that unrefereed booksand book chapters were excluded by the computer literature search pro-cedure. Thus, this search was limited to journal articles on the similar-
ity of twins' personality and intelligence. Table 1 displays the numberand percentage of studies per category. Note that 130 twin studies wereread for this meta-analysis. Of these 130 papers, 103 actually containedintraclass re or data that could be converted to intraclass re; these 103papers 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, wesearched more broadly than was necessary. We believe that the compre-hensiveness of the search was guaranteed by the broad descriptor termsused in the computer search. Certainly the search identified studies ona wide range of topics, from a wide range of periodicals. Although only13.4% of studies from the literature search were coded, it is importantto consider that all the studies excluded, with the exception of disserta-tions, were those that did not present relevant data on personality or
intelligence.Even if the search were not comprehensive, it would only be a prob-
lem if the identified studies were not representative of studies published,and there is no reason to suspect any bias. Some literatures—for exam-ple, that on sex differences—are biased with respect to which studiesare published (see Hall, 1987). This is referred to as the "file drawer"problem (Rosenthal, 1984), because unpublished, relevant studies canonly be located in the file drawers of researchers. However twin studiesare unlikely to be found in file drawers because twins have been consid-ered to be valuable subjects. In fact, even case studies are likely to bepublished (16% of studies identified in this computer search were casestudies). More important, the file drawer problem is not an issue here,because this is a study of a moderator, namely age.
228 K.. MCCARTNEY, M. HARRIS, AND F. BERNIERI
Coding the Studies
Three coders each read approximately one third of the studies and
extracted intraclass re separately for MZ and DZ twins for each relevantdependent variable. Coders recorded the number of male pairs, thenumber of female pairs, and the number of mixed pairs (for DZ twins).Three moderator variables were recorded: age per group, method ofzygosity determination (blood grouping vs. other), and type of report(self vs. parent). We had planned to use type of DZ twin (same sexvs. opposite sex) as an additional moderator; however, only 12 studiesincluded opposite-sex DZ twins (9 of the 12 studies contained data on
twin similarity for intelligence). We decided to include data from DZtwins that included mixed-sex pairs rather than lose these data; this mayhave resulted in a lower DZ intraclass correlation for some traits, al-though sex differences are far less likely for intelligence than for person-ality variables. Because the mixed-sex DZ data were from studies ofseven different dependent variables (see categories described in the fol-
lowing 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 affectthe moderator analyses for age.
Classification of the Dependent Variables
Dependent variables were classified via group consensus based on the
knowledge of the researchers and on descriptions by authors. Intelli-gence was subdivided into five categories: verbal intelligence, quantita-tive intelligence, performance intelligence, perception, and total IQ.
Personality-temperament was subdivided into eight categories: activ-ity-impulsivity,1 aggression, anxiety, dominance, emotionality, mascu-linity-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 ascreativity, altruism, religiosity, hypnotic susceptibility, and humor. Weexcluded one additional category, attachment, because it was measuredvery differently across studies (e.g., approach to stranger, approach tomother, crying, and so on).
Researchers often assessed a single construct with multiple measures(e.g., self-report and behavioral observation). In such cases, we com-puted a combined effect-size estimate using the Fisher's z, transforma-tion (Rosenthal, 1984, p. 27). This is preferable to including all effect
sizes from a given study separately, a procedure that would violate theindependence assumption that is essential for many meta-analytic pro-cedures.
Results
Mean Effect-Size Estimates
Table 2 presents mean intraclass rs separately for MZ and
DZ twins per dependent variable. Mean rs were calculated using
two methods: (a) giving each study unit weight, that is, the sim-
ple mean effect size across all studies, and (b) weighting the in-
traclass r for each study by the number of twin pairs for that
study. Because there was little difference between the results ob-
tained by using these two weighting strategies, we limit our-
selves to a discussion of the data obtained by using unit weight-
ing. 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-
ences between the two selection strategies, so we report the data
for all studies in order to simplify our presentation.
Note that there is no agreed-on test of significance to deter-
mine 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 ob-
servations within studies are not independent. The rs in Table
2 should, therefore, be treated as effect-size estimates and evalu-
ated accordingly, where .10 is low, .30 is moderate, and .50 is
large (Cohen, 1977).
Table 2 reveals three important findings. First, the MZ rs are
greater than the DZ rs by .22 for the combined intelligence vari-
ables and by .29 for the combined personality variables. Al-
though a combined personality variable may not be readily in-
terpretable, 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
similar to two other reviews that reported median intraclass rs.
Nichols (1978) reported a median intraclass r for general intelli-
gence 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
literature through 1971, whereas this meta-analysis covers the
years 1967 through 1985. Only nine studies in the present meta-
analysis 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 in-
traclass 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 over-
looked.
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 hy-
pothesized a genetic role in certain personality variables, most
notably sociability (A. Buss & Plomin, 1984) and behavioral
inhibition (Kagan, Reznick, & Snidman, 1988). Variables such
as masculinity-femininity and task orientation have typically
been considered as having strong socialization components.
The homogeneity of the intraclass rs for the personality vari-
ables included here, however, suggests that the various facets of
personality are not differentially affected by genetic or environ-
mental influences.
1 Although these two constructs no doubt seem distinct to some read-
ers, measures of activity and impulsivity were sometimes combined inresearch reports and are therefore combined here.
2 Rose (1988) found evidence for differential heritability of personal-ity traits on the Minnesota Multiphasic Personality Inventory; however,Loehlin and Nichols (1976) concluded that there is little evidence fordifferential heritability of personality on the California PsychologicalInventory.
GROWING UP AND GROWING APART 229
Table 2
Mean Inlradass rs for Monozygotic (MZ) andDizygotic (DZ)
Twins From All Studies Coded
Variable typeand variables
IntelligenceVerbalQuantitativePerformancePerceptionTotal IQ
M»
PersonalityActivity-impulsivityAggressionAnxietyDominanceEmotionalityMasculinity-femininitySociabilityTask orientation
M*
Numberof studies
29 a
829"I )42"
31"897
18'9
33'7
Weightedby study
MZ
.76
.71
.71
.55
.81
.72
.58
.49
.59
.50
.54
.50
.50
.42
.51
DZ
.47
.51
.47
.45
.59
.50
.22
.28
.18
.25
.19
.33.16.17
.22
Weightedby sample
MZ
.76
.74
.70
.55
.81
.72
.51
.49
.54
.51
.47
.52
.51
.44
.50
DZ
.48
.57
.47
.42
.61
.51
.20
.29
.19
.21
.15
.36
.19
.19
.22
" DZ results are based on I fewer studies. b Arithmetic mean calcu-lated on Fisher's z-transformed rs.
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 personal-
ity. An alternative explanation is that because personality mea-
sures are typically more unreliable than intelligence measures,
the personality correlations are therefore lower.
Age as a Moderator
The most straightforward way to examine the effect of a mod-
erator 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.
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 possi-
ble (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 anal-
yses, only the correlations between intraclass rs and untrans-
formed age are reported.
Only independent studies (i.e., no longitudinal or cross-sec-
tional studies) were used in the examination of moderator vari-
ables. 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 stud-
ies. Also, although data from one age group per study could
have been included, on the basis of some random selection pro-
cedure, we decided not to do so because we were concerned
about practice effects. Alternatively, we could have included the
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-
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-
dian of mean ages across studies varied somewhat. The corre-
lations of effect size and age for the intelligence variables show
that DZ twins become more dissimilar over time than MZ
twins; however, this difference is in large part accounted for by
the analysis of quantitative intelligence. The correlations of
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 ac-
cepted test of significance for these rs. They should be inter-
preted 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 sepa-
rately for MZ and DZ twins within the categories of intelligence
and personality, following the procedure outlined by Rosenthal
Table 3
Correlations Between Intraclass rs and Age of Twins
(From Independent Studies)
r
Variable type Number MZand variables of studies twins
IntelligenceVerbalQuantitativePerformancePerceptionTotal IQ
Mb
PersonalityActivity-impulsivityAggressionAnxietyDominanceEmotionalityMasculinity-femininitySociabilityTask orientation
M"
228
145
16*
14'8558"7
20°5
-.14-.13-.25-.64
.15
-.22
-.48-.09-.34
.67-.11-.81*-.24-.69
-.30
DZtwins
.10-.82-.36-.79-.25
-.50
-.33-.06-.49
.07
.30-.74
.26-.89
-.32
Medianage
10.010.5107.77.8
7.611.520.430.06.3
1616.528
Agerange
in years
2-846-416^tl6-201-59
1-507-497-307-501-507-503-501-50
Note. MZ = monozygotic; DZ = dizygotic.a DZ results are based on 1 fewer study. b Arithmetic mean calculatedon Fisher's z-transformed rs.
230 K. MCCARTNEY, M. HARRIS, AND F. BERNIERI
Table 4
Contrasts of the Effects of Twins'Age on Intraclass rs
(From Independent Studies)
Variable typeand variables
IntelligenceVerbalQuantitativePerformancePerceptionTotal IQ
Numberof studies
228
145
16"
Age contrast Z
MZ twins
-0.58-0.42-2.07**-0.89
1.00
DZ twins
0.29-2.28"-0.90-0.87-1.04
-0.09 -0.40
PersonalityActivity-impulsivityAggressionAnxietyDominanceEmotionalityMasculinity- femininitySociabilityTask orientation
M*
14'8558'7
20'5
-4.79***0.05
-1.91*2.44**
-0.56-2.95**-1.42-1.75*
-0.34
-3.53***-0.39
0.380.150.84
-1.76*0.83
-0.58
-0.39
Note. MZ = monozygotic; DZ = dizygotic." DZ results are based on 1 fewer study. " Arithmetic mean calculatedon Fisher's z-transformed rs.*p<.W. **p<.05. ***/)<.01.
and Rubin (1982). To create contrast weights, we simply sub-
tracted 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
based on many observations, which increases confidence in the
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
on two personality variables: activity-impulsivity and mascu-
linity-femininity. In addition, the age contrast on MZ twins was
significant for three other personality variables: anxiety, domi-
nance, and task orientation. The contrast on dominance, how-
ever, was positive, indicating increasing similarity for MZ twins
over time.3 For intelligence, there was one significant age con-
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-
ses are probably the result of points of high leverage in the com-
putation 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.
To summarize the results of these two analyses, both demon-
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-
tween twin similarity and age for activity-impulsivity and for
masculinity-femininity, whereas there is little association be-
tween similarity and age for aggression and for emotionality.
Methodological Moderators
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-
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 sci-
ence, 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 compro-
mise 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 consid-
ered in the following paragraphs for three dependent variables:
total IQ, sociability, and activity-impulsivity. Total IQ was se-
lected because it is the most robust measure of intelligence. So-
ciability and activity-impulsivity were selected because they are
based on the largest number of studies in the personality do-
main. 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.
Type of report. The vast majority of personality constructs
were measured by self-report. In 13 studies, personality was as-
sessed by parent report. Twelve of these studies concerned tem-
perament and 1 concerned sex roles. In 4 of the 12 studies, be-
havioral observations were collected in addition to parent re-
port. There is an association between age and report method for
some measures of personality. If parents of MZ twins are prone
to view their children as more similar (see Jones, 1955; Koch,
1966), then the association between age and report method
would be a confound. However, several studies have docu-
mented a lack of bias between parents' reports on their twins
and zygosity. Ratings of confusability of twins are not signifi-
cantly correlated with difference scores on four temperament
traits (Plomin, Willerman, & Loehlin, 1976). Moreover, moth-
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 sam-ple separately for MZ and DZ twins for each dependent variable. In-
spection of the data revealed that a single point of high leverage wasresponsible for the positive Z on dominance; the youngest subjects gen-erated the lowest intraclass rs on dominance in a unique behavioral rat-ings task. Inspection of other plots yielded no other points of noticeablyhigh leverage.
GROWING UP AND GROWING APART 231
Nevertheless, method of report remains controversial in twinstudies (Bates, 1980). For this reason, we dummy-codedmethod of report (self vs. parent) and correlated it with MZ reand DZ re for sociability and activity-impulsivity (intelligencewas never assessed via parent report).
For sociability, the correlation between method of report andtwin 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 similarthan self-reports for MZ twins and are less similar than self-reports for DZ twins.
For activity-impulsivity, the pattern of results was somewhatdifferent. The correlation between method of report and twinsimilarity was large and negative for both MZ twins (r = —.75,p < .01) and DZ twins (r = -.42, p > .20). For both types oftwins, intraclass rs were greater for parent reports than for self-reports. It is probable that parent reports are less valid than self-reports, because parents make two sets of ratings.
For this reason, correlations between intraclass rs and agewere computed again without data from parent reports. For ac-tivity-impulsivity there was actually a somewhat stronger ageeffect (see Table 3). For the eight self-report studies of MZ twins,the correlation between age and twin similarity was —.51; forthe seven self-report studies of DZ twins, the corresponding cor-relation was —.42. Thus, even with self-report data only, thereis decreasing twin similarity on activity-impulsivity with age.
For sociability, there was again little association between twinsimilarity and age for the self-report studies. For the 14 self-report studies, the correlation between age and twin similarityfor both MZ and DZ twins was -.02.
Age and reliability of measures. The reliability of measureschanges with age. Intelligence tests become more reliable withage, with the greatest change occurring between the preschooland early grade-school years (Anastasi, 1982). For personality,however, this change is less clear. For example, test-retest corre-lations for the California Psychological Inventory (CPI; Gough,1975), the most commonly used scale for adults in this set ofstudies, are comparable to those of the Emotionality, Activity,and Sociability Scale (EAS; A. Buss & Plomin, 1984), the mostcommonly used scale for children in these studies. For sociabil-ity, 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 measure-ment reliability works against the hypothesis that there is de-creasing similarity over time. For this reason, the correlationbetween age and twin similarity was examined in only thosestudies for which the mean age of subjects was 5 years or more.(Of course, this restricts the range of ages considered, whichmay in itself affect the analyses.) The results were quite similarto those reported in Table 3. For total IQ, the r for MZ twinswas .28; for DZ twins it was -.36. For sociability, the r for MZtwins was -.16; for DZ twins it was .00. For activity-impulsiv-ity, the r for MZ twins was - .42; for DZ twins it was - .27. Thus,age differences in assessment reliabilities do not appear to haveconfounded the results of this developmental meta-analysis.
A related problem for developmentalists is that the operation-alization of constructs changes over time. For example, intelli-gence 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
design. Similarly, sociable behaviors of 2-year-olds and 16-year-olds also differ. Differences in the operationalization and reli-ability of assessment tools for subjects of different ages are un-solved problems for developmentalists who study constancyand change in human development (Kagan, 1980). It is for thisreason that the statistical issues in the assessment of change havereceived great attention (Cronbach & Furby, 1970; Judd &Kenny, 1981; Richards, 1976).
Zygosity determination as a moderator. Blood grouping isthe most reliable method of zygosity determination. When 20genetic markers are analyzed in blood samples, accuracy ap-proaches 100% (Plomin et al., 1980). Less reliable methods in-clude ratings of picture similarity, comparison of fingerprints,and simply asking twins whether they are identical twins.
Zygosity was dummy-coded to reflect blood grouping versusother methods. We expected higher intraclass rs for MZ twinsand lower intraclass rs for DZ twins in studies using bloodgrouping, because this method would tend to purify the MZand DZ samples. Because there was no reason to expect differ-ences in the zygosity moderator to be associated with specifictraits, we performed contrasts on mean intelligence and meanpersonality.
For mean personality, as predicted, there was a trend for MZtwins to generate higher intraclass rs in studies using bloodgrouping (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 didnot moderate the effect sizes of either MZ (Z = -.83) or DZ(Z = .24) twins.
From the present set of analyses, there is no strong evidenceto suggest the methodological superiority of blood groupingwith respect to the prediction of intraclass rs. The cruder meth-ods of zygosity determination, which are highly correlated withblood grouping, perform well.
Components of Variance Analyses
As previously discussed, the computation of components ofvariance from twin data is controversial. Criticism has focusedon heritability (if). In twin studies, h2 is computed by doublingthe difference between MZ and DZ intraclass rs (see Plomin,1986, p. 15). A statistical concern with h2 is the relative unreli-ability of difference scores. The standard error of differencesbetween correlations is larger than the standard error of a sim-ple correlation. In addition, there are conceptual problems as-sociated 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 (andit is difficult to assess whether samples are indicative of popula-tions for many psychological traits); second, A2 requires quanti-tative definition of a trait (this is less of a problem with meta-analysis, where an estimate would be across measures); third,r? estimates assume the genetic and environmental componentsare additive and not correlated. This final point has been dis-puted in recent theoretical work (D. Buss, 1987; Plomin, De-Fries, & Loehlin, 1977; Scarr & McCartney, 1983)and in recentempirical work (Pederson, Plomin, McClearn, & Friberg,1988).
Environmental components of variance can also be esti-
232 K. MCCARTNEY, M. HARRIS, AND F. BERNIERI
Table 5
Correlations Between Components of Variance
and Age of Twins
Amount of data Heritability
All dataIntelligenceSociabilityActivity-impulsivity
Excluding data wheremean age is 5years or less
IntelligenceSociabilityActivity-impulsivity
Excluding parent report dataSociabilityActivity-impulsivity
.36-.46
.03
.52-.18-.29
.08
.09
Sharedenvironment
-.37.40
-.21
-.50.11.05
-.12-.39
Nonsharedenvironment
-.15.33.48
-.28.16.42
.02
.60
Nate. The monozygotic twin age weight was used in these reported anal-yses. Corresponding analyses with the dizygotic twin age weight werenearly identical.
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 environ-
ment (Wachs, 1983). For example, the shared environmental
effect (es2) is estimated by MZ, — h2; the nonshared environ-
mental 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.
To determine the source of decreasing twin similarity, age
was correlated with these three components of variance for in-
telligence, sociability, and activity-impulsivity (see Table 5).
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 anal-
yses must be viewed with caution because of the limitations,
outlined earlier, associated with components of variance analy-
ses. In addition, it is not clear how reliable these analyses are,
especially when they are based on so few data points. These
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
lesser extent ens2, decreased over time. For sociability, the re-
sults changed when either the preschool data or the parent re-
port data were excluded. In these cases, there was little evidence
for change of any sort. For activity-impulsivity, ens2 increased
over time and es2 decreased over time, especially for the analy-
ses of self-report data.
Discussion
The methodological purpose of this article has been to dem-
onstrate 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
of cross-sectional study. The major advantage may be that an
entire body of literature can be brought to bear on a develop-
mental issue. For this reason, developmental meta-analyses can
be particularly useful in orienting the focus of future longitudi-
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 addi-
tional moderator analyses that alternative hypotheses to those
associated with age can be considered. Here, two such modera-
tors were considered: type of report and reliability of assess-
ment. As with all meta-analyses, variables associated with the
soundness of the methodology should be considered, so that
good studies are not outweighed by bad ones. Here, one such
moderator was considered: method of zygosity determination.
The substantive purpose of this article has been to examine
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-
ment increases with age. We were able to assess the relative im-
portance of the shared and nonshared environments by recon-
ceptualizing twin studies as within-family studies and by deter-
mining that age contrasts in a meta-analysis could be used to
test a developmental hypothesis. The results of this meta-analy-
sis 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-
tain domains of personality—for example, activity-impulsivity
and masculinity-femininity—showed substantial change over
time. Other domains, such as anxiety and task orientation,
showed similar changes for MZ twins only. There was less agree-
ment between the correlational analysis and the contrast analy-
sis for intelligence than for personality. The correlations be-
tween mean age and effect size of study were comparable to
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
reports appear to bias ratings of temperament. Another moder-
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 personal-
ity variables. Other moderators studied here, such as age differ-
ences in reliability and method of zygosity determination, ap-
peared to have little, if any, effect. However, power in most anal-
yses was low. Although 103 studies were coded in this
investigation, more than half of the 13 variables were assessed
in fewer than 20 studies. This limitation weakens somewhat the
robustness of the findings. Nevertheless, it must be remembered
that each data point is based on multiple subjects in a study.
This robustness was demonstrated by the consistency be-
tween the average effect-size estimates reported here and the
median rs reported by Bouchard and McGue (1981) for intelli-
gence 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
GROWING UP AND GROWING APART 233
show that "a twin study is likely to find a difference betweenidentical and fraternal correlations of about .20 regardless ofthe 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 ob-taining heritability estimates on specific psychological indexesare unlikely to make any significant contribution.
Certainly, most twin and adoption studies show that the envi-ronment accounts for a substantial portion of variance (Loeh-lin, Willerman, and Horn, 1988). Our purpose here has notbeen to compute components of variance. However, age wascorrelated with components of variance in order to examinedevelopmental patterns. Two speculations can be made basedon these exploratory analyses. First, heritability seems to in-crease over time for IQ. This may reflect an age-related increasein 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 sharedenvironment decreased over time; the nonshared environmentincreased over time for activity-impulsivity. It was difficult toanalyze age-related change in components of variance with re-spect to sociability, because the pattern changed when the par-ent report data were eliminated.
Thus, the results of this developmental meta-analysis of twinstudies support recent developmental theory and recent familyresearch in that they demonstrate the importance of nonsharedexperiences generally (e.g., Plomin & Daniels, 1987). This isespecially impressive in this context: Twin studies probablyoverestimate the importance of the shared environment, be-cause twins no doubt experience more similar environmentsthan do other siblings (Plomin, 1986). In other words, this pat-tern may be greater for nontwin siblings.
Patterns associated with nonshared environmental effectsmay be complicated by the fact that there are probably two dis-tinct types. The nonshared environment consists of both non-systematic experiences (stochastic events) and systematic expe-riences. It may be that nonsystematic experiences lead todifferences and systematic experiences increase similarity whengenetic predispositions are shared.
There are some data on differential parental treatment tosupport this thesis. Lytton's (1977) observations of parent-child interaction with both MZ and DZ twins suggest that par-ems respond to differences between the twins based on actualrather than perceived zygosity. Dunn, Plomin, and Nettles(1985) found greater differences in maternal affection betweenadopted siblings, who are not genetically related, than betweenbiological siblings.
Yet if people make their own environments through probabi-listic associations with genetic predispositions, as Scarr and Mc-Cartney (1983) have suggested, then one might expect that MZtwins would become less dissimilar over time than DZ twins,because MZ twins would be expected to create similar nichesin life. The results of this meta-analysis are mixed on this issue.Although the correlational analysis shows that DZ twins be-come more dissimilar over time on intelligence, the contrastanalysis shows little evidence for change, in one direction or theother, for either MZ or DZ twins. For personality, the correla-tional analysis reveals a similar pattern of dissimilarity over
time for both MZ and DZ twins, although the contrast analysisshows many more significant effects for MZ twins.
An ad hoc explanation for why MZ twins would becomemore dissimilar over time than DZ twins is the greater need ofMZ twins to appear different. Schachter (1982) introduced theterm sibling deidentification to describe a process throughwhich family members might define siblings as different or con-trasting. Schachter and Stone (1985) found evidence for deiden-tification among same-sex siblings and among first-sibling pairs.Perhaps this happens because these children are more likely tobe compared with one another. Similarly, MZ twins, who arethe most likely of all sibling pairs to be compared with one an-other, may be more likely to deidentify than DZ twins, at leaston some measures of personality.
Thus, because there is little evidence that DZ twins becomemore dissimilar over time than MZ twins, it appears that non-systematic environmental effects might play a more dominantrole than systematic environmental effects. The implications ofthis conclusion for future research are challenging. One ap-proach might be to target certain environmental effects thatwould seem to be unrelated to genetic predispositions or sharedfamily experience, for example, being randomly placed in aclassroom with a particularly skilled teacher or being hospital-ized because of injury.
A challenge also lies in the nearly certain fact that many de-velopmental processes operate simultaneously. For example,the shared and nonshared environments each affect develop-ment, to some extent. In addition, siblings may both identifyand deidentify, to some extent. Moreover, these processes mayinteract differently for different traits and abilities duringdifferent developmental periods. As we search for the methodsto study multiple developmental processes, developmentalmeta-analysis will have increasing utility.
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Received July 28, 1988
Revision received May 29, 1989
Accepted June 16,1989 •