Gender differences in mathematical performance have received considerable scrutiny in the fields of sociology, economics and psychology. We analyse a large data-set of high school graduates who took a standardised mathematical test in Russia in 2011 (n = 738,456) and find no substantial difference in mean test scores across boys and girls.…

In most school achievement research, the relationships between achievement and explanatory variables follow the Newton and Einstein concept/principle and the viewpoint of the macro-observer: Deterministic measures based on the mean value of a sufficiently large number of schools. What if the relationships between achievement and explanatory…

The shortcomings of the proportion above cut (PAC) statistic used so prominently in the educational landscape renders it a very problematic measure for making correct inferences with student test data. The limitations of PAC-based statistics are more pronounced with cross-test comparisons due to their dependency on cut-score locations. A better…

Value-added models have been widely used to assess the contributions of individual teachers and schools to students' academic growth based on longitudinal student achievement outcomes. There is concern, however, that ignoring the presence of missing values, which are common in longitudinal studies, can bias teachers' value-added scores.…

The test of homogeneity developed by L. V. Hedges (1982) for the fixed effects model is frequently used in quantitative meta-analyses to test whether effect sizes are equal. Despite its widespread use, evidence of the behavior of this test for the less-than-ideal case of small study sample sizes paired with large numbers of studies is…

The second approach used by L. V. Hedges and L. Friedman (1993) in their reanalysis of Feingold's earlier results is conceptually equivalent and yields results consistent with the original interpretation. The first method yields results that are discrepant. Analyses of variations in tail effect sizes are planned. (SLD)

Feingold's reply illustrates that his steps in characterizing tail effect sizes are not the calculations the authors had imagined. Attempting to reproduce Feingold's calculations, the authors still often find themselves in disagreement with interpretations Feingold has placed in his table. (SLD)

The relationship between gender and mathematical achievement was investigated in 440 female and 480 male Norwegian third graders. Boys had higher test scores, but the effect size was small. Boys performed better in numeracy, mental arithmetic, and measurement problems. Marked gender differences were found at extreme tails of the distribution.…

Analyzes effect sizes in tails of distribution of scores in Feingold's study of joint effects of gender differences in mean and variability on 28 cognitive-ability scales. Effect sizes are smaller than Feingold assumed. Evaluates joint effect of gender differences by number of males and females in extreme score ranges. (SLD)