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Latent Growth Models for Count Outcomes: Specification, Evaluation, and Interpretation
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Daniel Seddig – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The latent growth model (LGM) is a popular tool in the social and behavioral sciences to study development processes of continuous and discrete outcome variables. A special case are frequency measurements of behaviors or events, such as doctor visits per month or crimes committed per year. Probability distributions for such outcomes include the…
Descriptors: Growth Models, Statistical Analysis, Structural Equation Models, Crime
Modeling Retest Effects in Developmental Processes Using Latent Change Score Models
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Rohit Batra; Silvia A. Bunge; Emilio Ferrer – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Studying development processes, as they unfold over time, involves collecting repeated measures from individuals and modeling the changes over time. One methodological challenge in this type of longitudinal data is separating retest effects, due to the repeated assessments, from developmental processes such as maturation or age. In this article,…
Descriptors: Children, Adolescents, Longitudinal Studies, Test Reliability
On Obtaining Estimates of the Fraction of Missing Information from Full Information Maximum Likelihood
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Savalei, Victoria; Rhemtulla, Mijke – Structural Equation Modeling: A Multidisciplinary Journal, 2012
Fraction of missing information [lambda][subscript j] is a useful measure of the impact of missing data on the quality of estimation of a particular parameter. This measure can be computed for all parameters in the model, and it communicates the relative loss of efficiency in the estimation of a particular parameter due to missing data. It has…
Descriptors: Computation, Structural Equation Models, Maximum Likelihood Statistics, Data
Latent Class Analysis with Distal Outcomes: A Flexible Model-Based Approach
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Lanza, Stephanie T.; Tan, Xianming; Bray, Bethany C. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
Although prediction of class membership from observed variables in latent class analysis is well understood, predicting an observed distal outcome from latent class membership is more complicated. A flexible model-based approach is proposed to empirically derive and summarize the class-dependent density functions of distal outcomes with…
Descriptors: Structural Equation Models, Monte Carlo Methods, Comparative Analysis, Statistical Analysis
Conducting Confirmatory Latent Class Analysis Using M"plus"
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Finch, W. Holmes; Bronk, Kendall Cotton – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Latent class analysis (LCA) is an increasingly popular tool that researchers can use to identify latent groups in the population underlying a sample of responses to categorical observed variables. LCA is most commonly used in an exploratory fashion whereby no parameters are specified a priori. Although this exploratory approach is reasonable when…
Descriptors: Structural Equation Models, Computer Software, Programming, Goodness of Fit
Mediation Analysis in a Latent Growth Curve Modeling Framework
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von Soest, Tilmann; Hagtvet, Knut A. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…
Descriptors: Statistical Analysis, Predictor Variables, Structural Equation Models, Adolescents
Modeling Relations among Discrete Developmental Processes: A General Approach to Associative Latent Transition Analysis
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Bray, Bethany C.; Lanza, Stephanie T.; Collins, Linda M. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
To understand one developmental process, it is often helpful to investigate its relations with other developmental processes. Statistical methods that model development in multiple processes simultaneously over time include latent growth curve models with time-varying covariates, multivariate latent growth curve models, and dual trajectory models.…
Descriptors: Structural Equation Models, Development, Statistical Analysis, Drinking
Testing Inequality Constrained Hypotheses in SEM Models
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van de Schoot, Rens; Hoijtink, Herbert; Dekovic, Maja – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Researchers often have expectations that can be expressed in the form of inequality constraints among the parameters of a structural equation model. It is currently not possible to test these so-called informative hypotheses in structural equation modeling software. We offer a solution to this problem using M"plus." The hypotheses are…
Descriptors: Structural Equation Models, Computer Software, Hypothesis Testing, Statistical Analysis
Regime Switching in the Latent Growth Curve Mixture Model
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Dolan, Conor V.; Schmittmann, Verena D.; Lubke, Gitta H.; Neale, Michael C. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
A linear latent growth curve mixture model is presented which includes switching between growth curves. Switching is accommodated by means of a Markov transition model. The model is formulated with switching as a highly constrained multivariate mixture model and is fitted using the freely available Mx program. The model is illustrated by analyzing…
Descriptors: Drinking, Adolescents, Evaluation Methods, Structural Equation Models
Modeling HIV Risk in Highly Vulnerable Youth
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Huba, G. J.; Panter, A. T.; Melchior, Lisa A.; Trevithick, Lee; Woods, Elizabeth R.; Wright, Eric; Feudo, Rudy; Tierney, Steven; Schneir, Arlene; Tenner, Adam; Remafedi, Gary; Greenberg, Brian; Sturdevant, Marsha; Goodman, Elizabeth; Hodgins, Antigone; Wallace, Michael; Brady, Russell E.; Singer, Barney; Marconi, Katherine – Structural Equation Modeling: A Multidisciplinary Journal, 2003
This article examines the structure of several HIV risk behaviors in an ethnically and geographically diverse sample of 8,251 clients from 10 innovative demonstration projects intended for adolescents living with, or at risk for, HIV. Exploratory and confirmatory factor analyses identified 2 risk factors for men (sexual intercourse with men and a…
Descriptors: Health Programs, Substance Abuse, Structural Equation Models, Risk