It can be seen from the table that the mean difference associated with sex is large; however, a large difference in mean performance between the gender categories also exists. The variability in mean mental rotation performance associated with the gender categories is graphically represented in Fig. 2.
Effect sizes. All subjects. The female vs. male effect size was d = 0.78. This value is consistent with the recent 3-D mental rotation studies reviewed by Linn & Petersen (1985) and Halpern (1992) and similar to Phillips’s (1979) original observations. The effect associated with perceived gender traits (median split technique) is shown in Table 3.
It should be noted that in this sample the effect sizes found with the androgynous subjects vs. feminine subjects and androgynous vs. undifferentiated were both d = 0.80, a comparable effect size with that of the sex variable. Thus, in this spatial task, self-perceived gender trait possession is associated with a relatively large effect size.
Female subjects. In the comparison of the gender categories, the maximum effect size obtained was d = 0.46 with androgynous vs. feminine subjects. Therefore, with female subjects only, the effect size is reduced.
Male subjects. In the comparison of the gender categories with male subjects, the maximum effect size was d = 1.08 with androgynous rs. undifferentiated subjects. With male subjects, therefore, the possession of distinct gender traits is associated with a relatively large effect size. This is shown in Fig. 3.
S & M task regression analysis. The following variables were employed as predictors in the (forward) stepwise regression analyses: Institute (FE or other), class (maths A-level or other A-level course), M (masculinity), F (femininity), M x F, M F, and sex (female or male). Two further variables which were included, M[sup2] and F[sup2], were employed as controls against ‘moderator effects’ (Lubinsky & Humphreys, 1990). The S & M final score was employed as the criterion.
Regression analysis. All subjects. The results of this analysis showed F(4,122) = 8.89, with p .84.
It can be noted from this analysis that the variable of sex is highly significant. However, the gender variable, M x F, adds to the model and is also significant in this analysis.
Female subjects. The obtained model showed F(2,119) = 6.08 with p .36.
Male subjects. The model obtained with this analysis showed F(3,50) = 5.46, with p .49.
Female subjects. With female subjects the model produced an F(2,92) = 6.78, with p .52.
Male subjects. The model achieved (Table 11) showed F(1,29) = 5.26, with p .17.
Therefore, while self-perceived gender traits were important for the GEFT regression analyses, it should be noted that relatively high performance was associated with either high masculine trait possession alone or a high masculine score in combination with a relatively low feminine score.
Combined spatial score
A final analysis was made with the S & M and GEFT scores combined. Each of the predictor variables identified above were employed in the stepwise regression and the criterion was the combined standardized scores from the S & M and GEFT performances.
The model produced an F(4,122) = 6.52, with p