Residual structures in growth models with ordinal outcomes

Resource Type: Reports & Papers
Author(s): Grimm, Kevin J.; Liu, Yu;
Date Issued: 2016
Description: Growth models allow for the study of within-person change and between-person differences in within-person change. Typically, these models are applied to continuous variables where the residuals are assumed to be normally distributed. With normally distributed residuals there are a variety of residual structures that can be imposed and tested, which have been shown to affect model fit and parameter estimation. This article concerns residual structures in growth models with binary and ordered categorical outcomes using the probit link function. Different residual structures and their appropriateness for growth data are discussed and their use is illustrated with longitudinal data collected as part of Head Start's Family and Child Experiences Survey 1997 Cohort. We close with recommendations for the specification and parameterization of growth models that use the probit link. (author abstract)
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Funder(s): National Science Foundation (U.S.)
Journal Title: Structural Equation Modeling
Volume Number: 23
Issue Number: 3
Page Range: 466-475
Topics: Research & Evaluation Methods > Research Methods > Data Analysis & Interpretation

Programs, Interventions & Curricula > Programs > Early Head Start/Head Start
Country: United States
ISSN: 1532-8007 Online
1070-5511 Paper
Peer Reviewed: yes
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Related Datasets

Head Start Family and Child Experiences Survey (FACES): 1997 Cohort [United States]

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