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New methods for the analysis of change.The best of both worlds: Combining autoregressive and latent curve models.

New methods for the analysis of change.: The best of both worlds: Combining autoregressive and... Discusses the autoregressive model (or "fixed effects Markov simplex model") and random coefficient growth curve models as being two analytic approaches to the theoretical conceptualization and statistical analysis of panel data. An extended empirical example is presented in order to illustrate the authors' ongoing efforts to synthesize these two models. They begin with a description of a theoretical substantive question that motivates the development of the synthesized model, they then present a review of the univariate and bivariate autoregressive simplex models followed by a general description of the univariate and bivariate latent curve models. The synthesis of the simplex and latent curve models is proposed for both the univariate and bivariate cases, and these are applied to the empirical data set to evaluate a series of questions relating to the developmental relation between antisocial behavior and depressive symptomatology. (PsycInfo Database Record (c) 2024 APA, all rights reserved) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

New methods for the analysis of change.The best of both worlds: Combining autoregressive and latent curve models.

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References (37)

Publisher
American Psychological Association
Copyright
Copyright © 2001 American Psychological Association
Pages
107–135
DOI
10.1037/10409-004
Publisher site
See Chapter on Publisher Site

Abstract

Discusses the autoregressive model (or "fixed effects Markov simplex model") and random coefficient growth curve models as being two analytic approaches to the theoretical conceptualization and statistical analysis of panel data. An extended empirical example is presented in order to illustrate the authors' ongoing efforts to synthesize these two models. They begin with a description of a theoretical substantive question that motivates the development of the synthesized model, they then present a review of the univariate and bivariate autoregressive simplex models followed by a general description of the univariate and bivariate latent curve models. The synthesis of the simplex and latent curve models is proposed for both the univariate and bivariate cases, and these are applied to the empirical data set to evaluate a series of questions relating to the developmental relation between antisocial behavior and depressive symptomatology. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

Published: Aug 31, 2004

Keywords: antisocial behavior; depressive symptomatology; development; autoregressive simplex models; latent curve models; synthesized model; random coefficient growth curve model

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