Multilevel modeling (MLM) is frequently used to detect cluster-level group differences in cluster randomized trial and observational studies. Group differences on the outcomes (posttest scores) are detected by controlling for the covariate (pretest scores) as a proxy variable for unobserved factors that predict future attributes. The pretest and…

I discuss three common practices that obfuscate or invalidate the statistical analysis of randomized controlled interventions in applied linguistics. These are (a) checking whether randomization produced groups that are balanced on a number of possibly relevant covariates, (b) using repeated measures ANOVA to analyze pretest-posttest designs, and…

Like many journals within education, for "Multicultural Learning and Teaching," this writer found little written on measurement, effect sizes, and confidence intervals; therefore, the purpose of this article is to address these factors. The effect of not addressing these issues is that a basic foundation of science cannot be established…