Open Journal of Psychiatry, 2011, 1, 15-19 OJPsych
doi:10.4236/ojpsych.2011.12003 Published Online July 2011 (http://www.SciRP.org/journal/OJPsych/).
Published Onl ine July 2011 in SciRes. http://www.scirp.org/journal/OJPsych
Spousal concordance in academic achievements and IQ: a
principal component analysis
Yue Pan1, Ke-Sheng Wang2*
1Department of Mathematics and Statistics, College of Arts and Sciences, East Tennessee State University, Johnson City, United
States;
2Department of Biostatistics and Epidemiology, College of Public Health, East Tennessee State University, Johnson City, United
States.
Received 10 May 2011; revised 8 June 2011; accepted 16 June 2011.
ABSTRACT
Assortative mating, the tendency for mate selection to
occur on the basis of similar traits plays an essential
role in understanding the genetic variation on aca-
demic achievements and intelligence (IQ), it is also an
important mechanism explaining spousal concor-
dance. We used a subset of The Collaborative Study
on the Genetics of Alcoholism sample to study the
mating patterns in 84 pairs of spouses from Cauca-
sian families with their academic achievements
(reading, spelling, arithmetic, vocabulary and com-
prehension) and IQ (verbal IQ, performance IQ and
full scale IQ). Simple correlation analysis showed
that 6 of these 8 traits revealed evidence of spousal
correlation (P < 0.05). The first principal component
(PC1) of husbands explains 73.61% for the variation
in the eight variables, which has high loadings from
reading, spelling, arithmetic, verbal IQ and full scale
IQ while PC1 of wives explains 72.86% for the varia-
tion in the eight variables, which has high loadings
from reading, spelling, verbal IQ and full scale IQ.
There was highly significant positive correlation be-
tween spouses by PC1 (P < 0.0001). The new variable
PC1 may be important in spousal concordance and
mate selection in society and act upon achievements
and intelligence levels.
Keywords: Academic Achievements; IQ; Spousal
Concordance; Principal Component Analysis
1. INTRODUCTION
Mate selection is a major biological event and whose
outcome is a substantial determinant of an individual’s
return on his/her whole reproductive investment [1].
Assortative mating, the tendency for mated pairs to be
more similar to each other phenotypically than would be
expected if they were married or mated at random, oc-
curs for a variety of phenotypic traits, including both
genetically determined traits and environmentally de-
termined traits [2]. Assortative mating plays an essential
role on society and the individual. It will increase the
population v ariance of a given trait and the propor tion of
individuals who are homozygous for the trait. At the
individual level, assortative mating can influence the
course and outcome of marriage, in addition to deter-
mining the genetic and biological makeup and parenting
of offspring [3].
Assortative mating has been shown for height [4-6],
attitude domain of personality [7-12], social factors
[13,14], smoking habits [15-17], and antisocial behavior
and psychiatric disorder [2,17-22]. Assortative mating,
the tendency for mate selection to occur on the basis of
similar traits plays an essen tial role in understand ing the
genetic variation on academic achievements and intelli-
gence (IQ), it is also an important mechanism explaining
spousal concordance. At present, assortative mating with
respect to IQ has been long standing interest to re-
searchers, there are number of analyses and studies [13,
14, 23-29]. However, few studies focus on the combina-
tion of IQ with academic achievements, and no study has
been found to use principal component analysis in as-
sessing spousal concordance of academic achievements
and IQ.
In the present study, we investigated the spousal con-
cordance with respect to eight variables which represent
the people’s academic achievements and IQ using both
simple correlation analysis and multivariate analysis.
2. METHODS
2.1. Subjects and Variable Selection
The Collaborative Study on the Genetics of Alcoholism

Y. Pan et al. / Open Journal of Psychiatry 1 (2011) 15-19
16
Table 1. Characteristics of husbands and wives, correlation analysis and paired-t-test.
Variable N husband-mean wife-mean corr-coef Pc T Pt
reading(standard) 84 99.66667 99.2619 0.60115 <0.0001 0.28 0.7784
spelling(standard) 84 93.79762 100.3571 0.5804 <0.0001 –4.03 0.0001
arithmetic(standard) 84 101.4048 99.72619 0.33865 0.0016 0.95 0.3429
vocabulary(scaled) 84 10.14286 10.25 0.43152 <0.0001 –0.33 0.7441
comprehension(scaled) 84 10.67857 9.92857 0.16864 0.1252 1.8 0.0749
verbal IQ(scaled) 84 105.1905 101.4524 0.27463 0.0115 2.05 0.044
performance IQ(scaled) 84 102.9286 102.2619 0.14197 0.1977 0.38 0.7015
full scale IQ(scaled) 84 104.381 101.8691 0.2809 0.0096 1.49 0.1404
N = number of individuals. Corr-coef = Correlation coefficient between spouses; Pc = p-value of correlation coefficient between spouses; T =
t-statistics of paired-t test. Pt = p-value of paired-t test between spouses.
(COGA) is a multisite collaboration with the goal of
identifying genes contributing to alcoholism and related
phenotypes [30]. A total of 2,282 individuals from 262
multiplex alcoholic families are available for genetic
analyses. Phenotypes include alcohol dependence, per-
sonal traits, academic achievements and IQ.
In order to conduct the analysis for achievement and
intelligence variables, we chose 8 variables in the COGA
data sets which represent the spouses’ standard achieve-
ments and intelligence level, as measured by the Wech-
sler Adult Intelligence Scale-Revised (WAIS-R). The
WAIS [31,32] is a traditional intelligence test with high
test-retest reliability, stability across different age spans,
concurrent and predictive validity and substantial herita-
bility [33]. The 8 variables are reading (standard), spel-
ling (standard), arithmetic (standard), vocabulary
(scaled), comprehension (scaled), verbal IQ (VIQ), per-
formance IQ (PIQ) and full scale IQ (FSIQ) [34,35].
From the 262 multiplex families, we found 84 indepen-
dent Caucasian spouse pairs with these 8 achievement
and intelligence variables ( Table 1).
2.2. Statistical Analysis
PROC UNIVARIATE was used to detect the normality
of these continuous traits and outlier. Paired t-test was
conducted to compare means of 8 variables between
husbands and wives. Then, spouse resemblance was as-
sessed by using Pearson correlation for each variable.
Finally, we used principal component analysis (PCA) to
generate PC scores as new variables to represent the
achievement and intelligence level for husbands and
wives, and test if there is spousal concordance for each
PC score. All the statistical analyses were performed
using SAS version 9.2.
3. RESULTS
3.1. Normality Test and Gender Difference
Based on the results of PROC UNIVARIATE, all 16
tests (8 variables for husbands and wives, respectively)
showed that all the variables were normally distributed
and no outlier was found. Because these traits were
normally distributed, we used paired t-test to test the
gender difference. The paired t-test showed that hus-
bands had lowe r score s for spelling and higher scores for
verbal IQ than wives (Table 1) while other variables did
not differ between male and female spouses.
3.2. Spousal Concordance Based on Simple
Correlation Analysis
Pearson correlation (Tabl e 1) showed that husbands and
wives had significant positive correlation for reading (r
= 0.60115, P < 0.001), spelling (r = 0.58040, P < 0.001),
arithmetic (r = 0.33865, P = 0.0016), vocabulary (r =
0.43152, P < 0.001), verbal IQ (r = 0.27463, P = 0.0115)
and full scale IQ (r = 0.28090, P = 0.0096) but no sig-
nificant correlations for comprehension (r = 0.16864, P
= 0.1252) and performance IQ (r = 0.14197, P =
0.1977).
3.3. Spousal Concordance Based on Correlation
Analysis using PC Scores
Because most of the variables were significantly corre-
lated with each other, we used principal component
analysis (PCA) to generate first and second principal
components (PC1 and PC2), which are independent each
other. Tabl e 2 showed the principal component loadings
for PC1 and PC2 in husband and wife groups. We found
that there was a 86.37% of accumulative contribution
ratio for male spouses by PC1 and PC2 while there was
a 87.99% of accumulative contribution ratio for female
spouses by PC1 and PC2, which revealed that PC1 and
PC2 could explain 86.37% (PC1 = 73.61%, PC2 =
12.76%) of the achievements and intelligence in male
spouses while 87.99% (PC1 = 72.86%, PC2 = 15.13%)
of the achievements and intelligence in female spouses.
In the PC1 cases, for husband variables, PC1 has high
loadings from spelling (0.488106), reading (0.432491),

Y. Pan et al. / Open Journal of Psychiatry 1 (2011) 15-19
17
Table 2. Principal components loadings for husbands and
wives.
Husband variables PC1 PC2
reading (standard) 0.432491 –0.196181
spelling (standard) 0.488106 –0.442378
arithmetic (standard) 0.394913 –0.458365
vocabulary (scaled) 0.081872 0.068215
comprehension (scaled) 0.071645 0.108926
verbal IQ (scaled) 0.422952 0.489498
performance IQ (scaled) 0.271721 0.309194
full scale IQ (scaled) 0.392671 0.451651
Wife variables PC1 PC2
reading (standard) 0.470387 –0.460293
spelling (standard) 0.480109 –0.442682
arithmetic (standard) 0.356364 0.068955
vocabulary (scaled) 0.07925 0.009375
comprehension (scaled) 0.059798 0.047292
verbal IQ (scaled) 0.396589 0.119958
performance IQ (scaled) 0.315482 0.658417
full scale IQ (scaled) 0.393151 0.370378
PC1 = First principal component. PC2 = Second principal component.
Figure 1. Relationship between husband and wife PC1 scores.
verbal IQ (0.422952), arithmetic (0.394913) and full
scale IQ (0.392671). For wife variables, PC1 has high
loadings from reading (0.470387), spelling (0.480109),
verbal IQ (0.39 6589) and fu ll scale IQ (0.39 315 1). In the
PC2 cases, for husband variables, PC2 has high loadings
from spelling (–0.442378), arithmetic (–0.458365), ver-
bal IQ (0.489498) and full scale IQ (0.451651). For wife
variables, PC2 has high loadings from performance IQ
(0.658417), reading (–0.460293), spelling (–0.442682)
and full scale IQ (0.370378).
Figure 1 showed there was a highly significant posi-
tive correlation between the PC1 values of paired hus-
bands and wives (r = 0.515, P < 0.0001, n = 84); whe-
reas the relationship in PC2 between husbands and wives
was weak (r = 0.1952, P = 0.0752).
4. DISCUSSION
The present analyses provide evidence of significant
spousal concordance in academic achievements and IQ
measured by WAIS-R. Simple correlation analyses
showed that 6 (reading, spelling, arithmetic, vocabulary,
verbal IQ and full scale IQ) of 8 traits in academic
achievements and IQ showed evidence of spousal corre-
lation (P < 0.05 ), while correlation analysis based on the
first principal component score (PC1 value) of 8 traits
further revealed highly significant spousal resemblance
(P < 0.0001).
Academic achievements and intelligence, which con-
sidered as important hereditary factors, have been com-
monly observed and studied in genetics. Assortative
mating by achievement or intelligence traits between
spouses, has been received much less attention despite
its potential importance as an indicator of mutual mate
choice [13,14, 23-29, 36]. It can affect the genetic struc-
ture of a population by increasing genetic variance and
also homozygosity, although only when few loci are
involved. It has been reported that all observed assorta-
tive mating in IQ and personal traits might well be due
to initial assortment [25]. Some indirect evidence is pre-
sented that assortative mating may codetermine patterns
of affectedness in dyslexia families with regarding to
reading and spelling [26]. Another study that measured
verbal and nonverbal intelligence showed that couples
were similar in almost all the measured traits, even after
controlling for age and education level and there was
moderate similarity in education and verbal intelligence
possibly due to assortative mating [16]. Wainwright et al.
(2005) used the univariate analysis to indicate a po sitive
phenotypic assortative mating and the phenotypic and
genetic correlations between the Queensland Core Skills
Test (QCST) and Verbal IQ were significantly stronger
than the phenotypic and genetic correlations between the
QCST a nd performance IQ [29].
This study has several strengths. First, we examined 8
traits in academic achievements and IQ and found 6 of
them showed significant spousal correlations. Secondly,
we used PC score to test the relationship for academic
achievements and IQ between spouses. PCA is a useful
statistical technique that has found application in fields
such as face recognition and image compression, and is a
common technique for finding patterns in data of high
dimension [37]. However, instead of using PCA to study
the achievements and IQ, other methods like univariate
analysis have been used to indicate a positive phenotypic
assortative mating [29] or ANCOVA for studying IQ in

Y. Pan et al. / Open Journal of Psychiatry 1 (2011) 15-19
18
childhood [28]. To our knowledge, our analysis using
PCA represents the first attempt to assess spousal con-
cordance in academic achievements and IQ. It has been
suggested that spouse similarity was found for tempera-
ment, personality and psychiatric symptomatology that
were largely independent highlights the necessity of si-
multaneous assessment of psychiatric domains in the
search for the underlying characteristics conditioning
nonrandom mate selection [11].
The findi ngs of this study als o ha ve several limitations.
The sample size is not large and the sample analyzed
was not a random population sample collected with the
primary goal of analyzing IQ. However, the mean and
standard deviation for IQ among the COGA sample and
the sibling correlation for the IQ measures, do not de-
viate considerably from published reports on unselected
samples [34].
In conclusion, the study confirms and extends pre-
vious studies relating to the spousal concordance in aca-
demic achievements and IQ. Regardless of the causes,
the presence of spousal concordance on achievements
and IQ aspects has important implications for genetic
studies in future research. An analysis of assortative
mating for academic achievements and IQ may help us
to understand the complex genetic and environmental
contributions to academic achievements and intelligence.
5. ACK NOWLEDGEMENTS
The Collaborative Study on the Genetics of Alcoholism (COGA) (H.
Begleiter, SUNY HSCB, Principal Investigator: T. Reich, Washington
University, Co-Principal Investigator) includes nine centers where data
collection, analysis, and/o r storage take place. The nine sites and P rin-
cipal Investigator and Co-Investigators are: Indiana University (T. -K.
Li, J. Nurnberger Jr., P. M. Conneally, H.J. Edenberg); University of
Iowa (R. Cro we, S. Kuperman); University of California at San Diego
(M. Schuckit); University of Connecticut (V. Hesselbrock); State Uni-
versity of New Yo rk, Health Sciences Center at Brooklyn (B. Porjesz,
H. Begleiter); Washington University in St. Louis (T. Reich, C. R.
Cloninger, J. Rice, A. Goate); Rutgers University (J. Tischfield); and
Southwest Foundation (L. Almasy). This national collaborative study i s
supported by NIH grant U10AA08403 from the National Institute on
Alcohol Abuse and Alcoholism (NIAAA). We acknowledge the con-
tributions of the COGA, supported by NIH Grants U10AA08401 and
U10AA08403 (NIAAA) and the contributions of all scientists who
have provided phenotypic and genotyping data. This study is part of
project “Genetic analysis of alcohol dependence and alcohol-related
phenotypes in the COGA sample” approved by IRB, East Tennessee
State University.
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