Binary outcomes are often analyzed in cluster randomized trials (CRTs) using logistic regression and cluster robust standard errors (CRSEs) are routinely used to account for the dependent nature of nested data in such models. However, CRSEs can be problematic when the number of clusters is low (e.g., < 50) and, with CRTs, a low number of…

Experiments in psychology or education often use logistic regression models (LRMs) when analyzing binary outcomes. However, a challenge with LRMs is that results are generally difficult to understand. We present alternatives to LRMs in the analysis of experiments and discuss the linear probability model, the log-binomial model, and the modified…

Studies analyzing clustered data sets using both multilevel models (MLMs) and ordinary least squares (OLS) regression have generally concluded that resulting point estimates, but not the standard errors, are comparable with each other. However, the accuracy of the estimates of OLS models is important to consider, as several alternative techniques…

Research has suggested that relatively older children are more likely to be identified as gifted and talented students compared with their younger peers. Such a phenomenon disadvantages the youngest students while at the same time confers additional advantages to the older students as a result of receiving specialized and/or extra instruction. The…

Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…

Students involved in bullying experience mental health issues and negative psychosocial outcomes. Few studies have investigated how teacher-student relationships (TSRs) may buffer the negative outcomes experienced by students involved in bullying. To investigate the moderating role of TSRs with bullying involvement status and psychosocial…

Districts have been engaged in efforts to reduce "differential processing" of discipline-referred students based on their racial backgrounds. They strive for fair assignment of exclusionary consequences across racial groups. The current study examines discipline records for one academic year in an urban school district (N = 9,039…

School climate is widely recognized as an important factor in promoting student academic achievement. The current study investigated the hypothesis that a demanding and supportive school climate, based on authoritative school climate theory, would serve as a protective factor for students living with 1 or no parents at home. Using a statewide…

The purpose of this Methodological Brief is to present a brief primer on logistic regression, a commonly used technique when modeling dichotomous outcomes. Using data from the National Education Longitudinal Study of 1988 (NELS:88), logistic regression techniques were used to investigate student-level variables in eighth grade (i.e., enrolled in a…

Clustered data (e.g., students within schools) are often analyzed in educational research where data are naturally nested. As a consequence, multilevel modeling (MLM) has commonly been used to study the contextual or group-level (e.g., school) effects on individual outcomes. The current study investigates the use of an alternative procedure to…

This study investigated the differential and persistent effects of a state-funded pre-K program, the Virginia Preschool Initiative (VPI). We analyzed data from a cohort of over 60,000 students nested in approximately 1000 schools from the beginning of kindergarten to the end of first grade using two-level hierarchical logistic regression models.…