Intensive longitudinal data is increasingly used to study state-like processes such as changes in daily stress. Measures aimed at collecting such data require the same level of scrutiny regarding scale reliability as traditional questionnaires. The most prevalent methods used to assess reliability of intensive longitudinal measures are based on…

This study examined the effect of similar vs. dissimilar proficiency distributions on uniform DIF detection on a statewide eighth grade mathematics assessment. Results from the similar- and dissimilar-ability reference groups with an SWD focal group were compared for four models: logistic regression, hierarchical generalized linear model (HGLM),…

The current simulation study examined the effects of Item Parameter Drift (IPD) occurring in a short scale on parameter estimates in multilevel models where scores from a scale were employed as a time-varying predictor to account for outcome scores. Five factors, including three decisions about IPD, were considered for simulation conditions. It…

The assessment of noncognitive traits is challenging due to possible response biases, "subjectivity" and "faking." Standardized third-party evaluations where an external evaluator rates an applicant on their strengths and weaknesses on various noncognitive traits are a promising alternative. However, accurate score-based…

The idea that test scores may not be valid representations of what students know, can do, and should learn next is well known. Person fit provides an important aspect of validity evidence. Person fit analyses at the individual student level are not typically conducted and person fit information is not communicated to educational stakeholders. In…

In this article, we discuss and illustrate two centering and anchoring options available in differential item functioning (DIF) detection studies based on the hierarchical generalized linear and generalized linear mixed modeling frameworks. We compared and contrasted the assumptions of the two options, and examined the properties of their DIF…

Using a sample of schools testing annually in grades 9-11 with a vertically linked series of assessments, a latent growth curve model is used to model test scores with student intercepts and slopes nested within school. Missed assessments can occur because of student mobility, student dropout, absenteeism, and other reasons. Missing data…

This study examines the use of cross-classified random effects models (CCrem) and cross-classified multiple membership random effects models (CCMMrem) to model rater bias and estimate teacher effectiveness. Effect estimates are compared using CTT versus item response theory (IRT) scaling methods and three models (i.e., conventional multilevel…

Teacher and school accountability systems based on high-stakes tests are ubiquitous throughout the United States and appear to be growing as a catalyst for reform. As a result, educators have increased the proportion of instructional time devoted to test preparation. Although guidelines for what constitutes appropriate and inappropriate test…