A critique of: Voyer, D., Voyer, S., & Bryden, M.P.(1995). Psychological Bulletin 117 , p.250-270.

1. Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. A critique of: Voyer, D., Voyer, S., & Bryden, M.P.(1995). Psychological Bulletin 117, p.250-270.

2. Sex and Spatial Ability Sex difference in spatial abilities: • Sex accounted for 5% of variance in spatial tasks. Other explanations/predictors of the difference: • Handedness, maturation rate, & birth order.

3. Categories of Spatial Abilities(Used as a moderator in this meta-analysis) • Mental rotation Lynn & Petersen (1985)

4. 2. Spatial Perception

5. 3. Spatial Visualization

6. Meta-analytic Procedure • Inclusion criteria: • Published studies that used a well-established spatial ability test (5+ studies) • Published between 1974-1993 • Found 310 effect sizes, 286 entered into meta-analysis

7. File Drawer Problem • Solution: • Calculate the number of studies necessary to offset findings at the .05 level. • Rosenthal (1980) • Arrive at a failsafe value.

8. Analysis Procedure Used Cohen’s d when means & SDs were available. Used Wolf’s formulae when t, χ2, p, F, was available. Hierarchical Approach: • Overall analysis of magnitude and homogeneity of sex differences. • Partition effect sizes by ability type and age of participants. • Partition effect sizes by type of test, then procedural variables.

9. Results • Weighted d=0.37 (z=2.62, p<.01). • Males are better at these spatial ability tasks than are females. • Heterogeneous effect sizes ( χ2(285,N=286)=1370.49, p<.001). • After partitioning effect sizes into spatial tasks: • Significant reduction in heterogeneity, but still heterogeneous ( χ2(2,N=286)= 410.09, p<.001). • Mental rotation category is significant: (d=0.56,p<.05). • Spatial perception is significant: (d=0.44, p<.05). • Spatial visualization category is not significant.

10. Partitioning by age: • reduced heterogeneity on all three spatial tasks • There’s still significant heterogeneity. • Partitioning on procedural variables: • Significantly reduced heterogeneity for 2 of the 12 tests.

11. Sex differences and age • Weighted regression analysis • Age = continuous predictor • estimated by mean age of studies or calculated from grade-in-school. • Partialed-out year of publication. • There is a linear increase in sex differences with age: • (r=0.263, p<.01).

12. Sex differences over time Problem: Changes in society might impact effect sizes. • Partial out year of birth rather than age. • more recently born show a smaller difference in spatial abilities (but n.s.)

13. Outcomes • They partialed-out moderators to achieve homogeneity of variance. • Examined effect sizes across age and time. • Found Sex differences to exist. • File-drawer problem is not plausible in this case (failsafe=170,000).

14. Cautions / Problems / Caveats / Critiques Partitioning based on age of participants. Effect sizes vary greatly from test to test. Sex differences vary by category. “File Drawer Problem”… problem. Wolf technique bad