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Sex Differences in Spatial Abilities: A Meta-Analysis

This study explores the magnitude of sex differences in spatial abilities, considering critical variables such as handedness, maturation rate, and birth order. Results show males outperform females in spatial tasks. Age and procedural variables influence heterogeneity in findings. The analysis reveals a linear increase in sex differences with age. The study addresses the file drawer problem and critiques the Wolf technique.

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Sex Differences in Spatial Abilities: A Meta-Analysis

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  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

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