Multiple imputation methods can generally be divided into two broad frameworks: joint model (JM) imputation and fully conditional specification (FCS) imputation. JM draws missing values simultaneously for all incomplete variables using a multivariate distribution, whereas FCS imputes variables one at a time from a series of univariate conditional…

Researchers are often interested in whether the effects of an intervention differ conditional on individual- or group-moderator variables such as children's characteristics (e.g., gender), teacher's background (e.g., years of teaching), and school's characteristics (e.g., urbanity); that is, the researchers seek to examine for whom and under what…

This note is concerned with examining the relationship between within-group and between-group variances in two-level nested designs. A latent variable modeling approach is outlined that permits point and interval estimation of their ratio and allows their comparison in a multilevel study. The procedure can also be used to test various hypotheses…

Multiple imputation (MI) can be used to address missing data at Level 2 in multilevel research. In this article, we compare joint modeling (JM) and the fully conditional specification (FCS) of MI as well as different strategies for including auxiliary variables at Level 1 using either their manifest or their latent cluster means. We show with…

Multilevel models (MLMs) have proven themselves to be very useful in social science research, as data from a variety of sources is sampled such that individuals at level-1 are nested within clusters such as schools, hospitals, counseling centers, and business entities at level-2. MLMs using restricted maximum likelihood estimation (REML) provide…

Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…

We compared students' performance on a paper-based test (PBT) and three computer-based tests (CBTs). The three computer-based tests used different test navigation and answer selection features, allowing us to examine how these features affect student performance. The study sample consisted of 9,698 fourth through twelfth grade students from across…

Bullying is the most common form of school violence and is associated with a range of negative outcomes, including traumatic responses. This study used hierarchical linear modeling to examine the multilevel moderating effects of school climate and school level (i.e., elementary, middle, and high schools) on the association between bullying…

We present three strategies to replace the null hypothesis statistical significance testing approach in psychological research: (1) visual representation of cognitive processes and predictions, (2) visual representation of data distributions and choice of the appropriate distribution for analysis, and (3) model comparison. The three strategies…

The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

Statway® is an accelerated developmental mathematics intervention program for college students who are not yet prepared to succeed in a college-level math course. The Carnegie Foundation for the Advancement of Teaching created the initiative to increase student success rates in developmental mathematics and subsequent credit-bearing, college-level…

Research on school leadership suggests that both principal and teacher leadership are important for school improvement. However, few studies have studied the interaction of principal and teacher leadership as separate but linked systems in how they relate to student outcomes. In this study, we examine how leadership pathways are related in the…

Research on school leadership suggests that both principal and teacher leadership are important for school improvement. However, few studies have studied the interaction of principal and teacher leadership as separate but linked systems in how they relate to student outcomes. In this study, we examine how leadership pathways are related in the…

In sport and exercise research, examining both within- and between-individual variation is crucial. The ability to investigate change both within competitive events and across a competitive season is a priority for many sport researchers. The aim of this article is to demonstrate an approach to analyzing intensive longitudinal data collected…

The effects of mean ability difference (MAD) and short tests on the performance of various DIF methods have been studied extensively in previous simulation studies. Their effects, however, have not been studied under multilevel data structure. MAD was frequently observed in large-scale cross-country comparison studies where the primary sampling…