Simulation studies are needed to investigate how many score categories are sufficient to treat ordered categorical data as continuous, particularly for bifactor models. The current simulation study aims to address such needs by investigating the performance of estimation methods in the bifactor models with ordered categorical data. Results support…

In health technology assessment, matching-adjusted indirect comparison (MAIC) is the most common method for pairwise comparisons that control for imbalances in baseline characteristics across trials. One of the primary challenges in MAIC is the need to properly account for the additional uncertainty introduced by the matching process. Limited…

As the theme of the 2022 annual meeting of the American Education Research Association, cultivating equitable education systems has gained renewed attention amid an increasingly diverse society. However, systemic inequalities persist for traditionally underserved student populations. As a way to better address diverse students' needs, it is of…

Maxwell, Cole, and Mitchell (2011) demonstrated that simple structural equation models, when used with cross-sectional data, generally produce biased estimates of meditated effects. I extend those results by showing how simple structural equation models can produce biased estimates of meditated effects when used even with longitudinal data. Even…

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

The aim of this work was to determine, in terms of Type I and Type II error rates, the risks of applying various statistical procedures for evaluating differential item functioning. To this end, the authors carried out a simulation study in which the Mantel-Haenszel and SIBTEST procedures were applied in conjunction. The variables manipulated were…

DETECT, the acronym for Dimensionality Evaluation To Enumerate Contributing Traits, is an innovative and relatively new nonparametric dimensionality assessment procedure used to identify mutually exclusive, dimensionally homogeneous clusters of items using a genetic algorithm ( Zhang & Stout, 1999). Because the clusters of items are mutually…

Often quantitative data in the social sciences have only ordinal justification. Problems of interpretation can arise when least squares multiple regression (LSMR) is used with ordinal data. Two ordinal alternatives are discussed, dominance-based ordinal multiple regression (DOMR) and proportional odds multiple regression. The Q[superscript 2]…

Purpose: This research provides state policy makers and others interested in developing needs-based reimbursement models for Medicaid-funded assisted living with an evaluation of different methodologies that affect the structure and outcomes of these models. Design and Methods: We used assessment data from Medicaid-enrolled assisted living…