In any meta-analysis, it is critically important to report the dispersion in effects as well as the mean effect. If an intervention has a moderate clinical impact "on average" we also need to know if the impact is moderate for all relevant populations, or if it varies from trivial in some to major in others. Or indeed, if the…

Equating error is usually small relative to the magnitude of measurement error, but it could be one of the major sources of error contributing to mean scores of large groups in educational measurement, such as the year-to-year state mean score fluctuations. Though testing programs may routinely calculate the standard error of equating (SEE), the…

A wide variety of methodological choices and situations can affect the quality of peer nomination measurements but have not received adequate study. This article begins by focusing on systematic nominator missingness as an example of one such situation. We reanalyzed findings from a recent study by Bukowski, Dirks, Commisso, Velàsquez, and Lopez…

The present study describes an R function that implements six corrective procedures developed by Bartlett, Swain, and Yuan in the correction of 21 statistics associated with the omnibus Chi-square test, the residuals, or fit indices in confirmatory factor analysis (CFA) and structural equation modeling (SEM).

Recently, Picho-Kiroga (2021) published a meta-analysis on the effect of stereotype threat on females. Their conclusion was that the average effect size for stereotype threat studies was d = .28, but that effects are overstated because the majority of studies on stereotype threat in females include methodological characteristics that inflate the…

Effectively teaching scientific reasoning requires an understanding of the challenges students face when learning these skills. We designed an assessment that measures undergraduate student abilities to form hypotheses, design experiments, and interpret data from experiments in cellular and molecular biology. The assessment uses…