The effects of selection and variability in studies of gender differences

Participation Rates and Maximal Performance: A Log-Linear Explanation for Group Differences, Such as Russian and Male Dominance in Chess

Can the superiority of some countries and groups at certain activities be explained solely by the relative sizes of the participating populations? We focus on the expected highest achievement, max, as a function of the participating group's size For several relevant statistical distributions, max can be shown to be approximately log-linear in sample size, with a slope of about 0 7 SD units We use this relation (max is log-linear ~0 7 MILL7) to examine differences in performance in chess by men and women and by different countries The expected differences under MILL7 are very close to the observed differences We also examine the implications of MILL7 for the interpretation of other group differences and discuss its limitations

On the Importance of Tail Ratios for Psychological Science

Even small group-mean differences (whether combined with variance differences or not) or variance differences alone (absent mean differences) can generate marked and sometimes surprising imbalances in the representation of the respective groups compared in the distributional tail regions. Such imbalances in group representation, quantified as tail ratios, have general importance in the context of any threshold, susceptibility, diathesis-stress, selection, or similar models (including the study of sex differences), as widely conceptualized and applied in the psychological, social, medical, and biological sciences. However, commonly used effect-size measures, such as Cohen's d, largely exploit data information around the center of distributions, rather than from the tails, thereby missing potentially important patterns found in the tail regions. This account reviews the background and history of tail ratios, emphasizes their importance for psychological research, proposes a consensus approach for defining and interpreting them, introduces a tail-ratio calculator, and outlines future research agenda.

Sex differences in mental test scores, variability, and numbers of high-scoring individuals

Sex differences in central tendency, variability, and numbers of high scores on mental tests have been extensively studied. Research has not always seemed to yield consistent results, partly because most studies have not used representative samples of national populations. An analysis of mental test scores from six studies that used national probability samples provided evidence that although average sex differences have been generally small and stable over time, the test scores of males consistently have larger variance. Except in tests of reading comprehension, perceptual speed, and associative memory, males typically outnumber females substantially among high-scoring individuals.