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Bolin, Jocelyn H.; Finch, W. Holmes; Stenger, Rachel – Educational and Psychological Measurement, 2019
Multilevel data are a reality for many disciplines. Currently, although multiple options exist for the treatment of multilevel data, most disciplines strictly adhere to one method for multilevel data regardless of the specific research design circumstances. The purpose of this Monte Carlo simulation study is to compare several methods for the…
Descriptors: Hierarchical Linear Modeling, Computation, Statistical Analysis, Maximum Likelihood Statistics
Finch, W. Holmes; Shim, Sungok Serena – Educational and Psychological Measurement, 2018
Collection and analysis of longitudinal data is an important tool in understanding growth and development over time in a whole range of human endeavors. Ideally, researchers working in the longitudinal framework are able to collect data at more than two points in time, as this will provide them with the potential for a deeper understanding of the…
Descriptors: Comparative Analysis, Computation, Time, Change
Finch, W. Holmes – Applied Psychological Measurement, 2012
Increasingly, researchers interested in identifying potentially biased test items are encouraged to use a confirmatory, rather than exploratory, approach. One such method for confirmatory testing is rooted in differential bundle functioning (DBF), where hypotheses regarding potential differential item functioning (DIF) for sets of items (bundles)…
Descriptors: Test Bias, Test Items, Statistical Analysis, Models
Finch, W. Holmes; French, Brian F. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
The purpose of this simulation study was to assess the performance of latent variable models that take into account the complex sampling mechanism that often underlies data used in educational, psychological, and other social science research. Analyses were conducted using the multiple indicator multiple cause (MIMIC) model, which is a flexible…
Descriptors: Causal Models, Computation, Data, Sampling
Finch, W. Holmes – Educational and Psychological Measurement, 2011
Missing information is a ubiquitous aspect of data analysis, including responses to items on cognitive and affective instruments. Although the broader statistical literature describes missing data methods, relatively little work has focused on this issue in the context of differential item functioning (DIF) detection. Such prior research has…
Descriptors: Test Bias, Data Analysis, Item Response Theory, Regression (Statistics)
French, Brian F.; Finch, W. Holmes – Structural Equation Modeling: A Multidisciplinary Journal, 2006
Confirmatory factor analytic (CFA) procedures can be used to provide evidence of measurement invariance. However, empirical evaluation has not focused on the accuracy of common CFA steps used to detect a lack of invariance across groups. This investigation examined procedures for detection of test structure differences across groups under several…
Descriptors: Factor Analysis, Structural Equation Models, Evaluation Criteria, Error of Measurement