The
Distance Between Mars and Venus: Measuring Global Sex Differences in
Personality
Marco Del
Giudice, Tom Booth, and Paul Irwing (January 2012)
Abstract
Background
Sex differences in personality are
believed to be comparatively small. However, research in this area
has suffered from significant methodological limitations. We advance
a set of guidelines for overcoming those limitations: (a) measure
personality with a higher resolution than that afforded by the Big
Five; (b) estimate sex differences on latent factors; and (c) assess
global sex differences with multivariate effect sizes. We then apply
these guidelines to a large, representative adult sample, and obtain
what is presently the best estimate of global sex differences in
personality.
Methodology/Principal Findings
Personality
measures were obtained from a large US sample (N = 10,261) with the
16PF Questionnaire. Multigroup latent variable modeling was used to
estimate sex differences on individual personality dimensions, which
were then aggregated to yield a multivariate effect size
(Mahalanobis D).
We found a global effect size D =
2.71, corresponding to an overlap of only 10% between the male and
female distributions. Even excluding the factor showing the largest
univariate ES, the global effect size was D =
1.71 (24% overlap). These are extremely large differences by
psychological standards.
Significance
The
idea that there are only minor differences between the personality
profiles of males and females should be rejected as based on
inadequate methodology.
Figure 1. The magnitude of global sex differences in personality, estimated with different methods from the same dataset.The effect size (ES) increases dramatically as better methods are employed. The male-female overlap (right-hand axis) is calculated on the joint distribution assuming multivariate normality.
Figure 1. The magnitude of global sex differences in personality, estimated with different methods from the same dataset.The effect size (ES) increases dramatically as better methods are employed. The male-female overlap (right-hand axis) is calculated on the joint distribution assuming multivariate normality.
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