Identifying items with differential item functioning (DIF) in an assessment is a crucial step for achieving equitable measurement. One critical issue that has not been fully addressed with existing studies is how DIF items can be detected when data are multilevel. In the present study, we introduced a Lord's Wald X[superscript 2] test-based…

Developmental researchers commonly utilize longitudinal data to decompose reciprocal and dynamic associations between repeatedly measured constructs to better understand the temporal precedence between constructs. Although the cross-lagged panel model (CLPM) is commonly used in developmental research, it has been criticized for its potential to…

Experimental evaluations that involve the educational system usually involve a hierarchical structure (students are nested within classrooms that are nested within schools, etc.). Concerns about contamination, where research subjects receive certain features of an intervention intended for subjects in a different experimental group, have often led…

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…

In a recently published meta-analysis, Tran, Sanchez, Arellano, and Swanson (2011) synthesized 13 studies that permitted assessment of characteristics of children who were adequate and inadequate responders to instruction. The authors indicated that "[t]he central question addressed in this review is whether individual differences in…

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

We explored possible cognitive, behavioral, emotional, and physiological risk markers for sleep disturbance in children with autism spectrum disorders. Data from 1,583 children in the Autism Treatment Network were analyzed. Approximately 45 potential predictors were analyzed using hierarchical regression modeling. As medication could confound…

The following article provides a brief primer and overview of multilevel and hierarchical linear modeling. The school-effects model with random effects is illustrated with a heuristic dataset. Finally, recommendations are presented for researchers studying learning disabilities who would like to utilize this methodology.