The present study aimed to examine how to improve the effectiveness of moral exemplar-applied interventions based on the pillars of the self-determination theory framework, autonomy, competence, and relatedness. Past research has mainly focused on the relatedness and attainability of moral exemplars for predicting motivation outcomes. The data for…

Hierarchical linear modeling (HLM) has been recommended as a meta-analytic technique for the quantitative synthesis of single-case experimental design (SCED) studies. The HLM approach is flexible and can model a variety of different SCED data complexities, such as intervention heterogeneity. A major advantage of using HLM is that participant…

This study investigated the power of two-level hierarchical linear modeling (HLM) to explain variability in intervention effectiveness between participants in context of single-case experimental design (SCED) research. HLM is a flexible technique that allows the inclusion of participant characteristics (e.g., age, gender, and disability types) as…

Background: Counts are familiar outcomes in education research settings, including those involving tests of interventions. Clustered data commonly occur in education research studies, given that data are often collected from students within classrooms or schools. There is a wide array of distributions and models that can be used for clustered…

Many methods are used to measure interrater reliability for studies where each target receives ratings by a different set of judges. The purpose of this study is to explore the use of hierarchical modeling for estimating interrater reliability using the intraclass correlation coefficient. This study provides a description of how the ICC can be…

When analyzing large-scale assessments (LSAs) that use complex sampling designs, it is important to account for probability sampling using weights. However, the use of these weights in multilevel models has been widely debated, particularly regarding their application at different levels of the model. Yet, no consensus has been reached on the best…

Educators commonly use school climate survey scores to inform and evaluate interventions for equitably improving learning and reducing educational disparities. Unfortunately, validity evidence to support these (and other) score uses often falls short. In response, Whitehouse et al. proposed a collaborative, two-part validity testing framework for…

Hierarchical linear modeling (HLM) is often used to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system. However, if a prior academic achievement measure is missing in a HLM model, biased estimates may occur on the effects of student SES and school SES. Phantom effects describe…

This investigation examines the efficacy of multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) over fixed-effects models when performing intersectional studies. The research questions are as follows: (1) What are typical strata representation rates and outcomes on physics research-based assessments? (2) To what…

Longitudinal assessment is a type of assessment involving repeated measures over a period to evaluate whether and when an attribute (e.g., ability, skill) changes. Thus, change detection is of central interest in longitudinal assessment. In the assessment setting, change in the desired direction (typically upward) is often referred to as…

Deciding which random effects to retain is a central decision in mixed effect models. Recent recommendations advise a maximal structure whereby all theoretically relevant random effects are retained. Nonetheless, including many random effects often leads to nonpositive definiteness. A typical remedy is to simplify the random effect structure by…

This meta-analysis examined the association of birth order and divergent thinking (DT). The main purpose was to examine how ordinal position (only, first, middle, or last-born) is related to creativity. The results from 27 studies (k= 222; N = 4,690) were analyzed using a multilevel approach. Because some previous studies compared first- vs.…

Standard item response theory (IRT) models have been extended with testlet effects to account for the nesting of items; these are well known as (Bayesian) testlet models or random effect models for testlets. The testlet modeling framework has several disadvantages. A sufficient number of testlet items are needed to estimate testlet effects, and a…

This study examined the relationships between school-level school climate and race differences in student grades, accounting for school sociodemographic composition. We found that schools with more positive school climates had smaller race differences in student self-reported grades. The moderating effect of school climate remained after…

School climate surveys are central to school improvement and principal evaluation policies. The quality of school climate has been linked both to student achievement and to teacher retention. Oftentimes, policymakers and practitioners are concerned with monitoring change in school climate quality in each academic year. Such applications assume…