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McNeish, Daniel; Harring, Jeffrey R. – Grantee Submission, 2021
Growth mixture models (GMMs) are a popular method to uncover heterogeneity in growth trajectories. Harnessing the power of GMMs in applications is difficult given the prevalence of nonconvergence when fitting GMMs to empirical data. GMMs are rooted in the random effect tradition and nonconvergence often leads researchers to modify their intended…
Descriptors: Growth Models, Classification, Posttraumatic Stress Disorder, Sample Size
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Lee, Daniel Y.; Harring, Jeffrey R.; Stapleton, Laura M. – Journal of Experimental Education, 2019
Respondent attrition is a common problem in national longitudinal panel surveys. To make full use of the data, weights are provided to account for attrition. Weight adjustments are based on sampling design information and data from the base year; information from subsequent waves is typically not utilized. Alternative methods to address bias from…
Descriptors: Longitudinal Studies, Research Methodology, Research Problems, Data Analysis