The Cusp Catastrophe Model as Cross-Sectional and Longitudinal Mixture Structural Equation Models

被引:31
|
作者
Chow, Sy-Miin [1 ]
Witkiewitz, Katie [2 ]
Grasman, Raoul P. P. P. [3 ]
Maisto, Stephen A. [4 ]
机构
[1] Penn State Univ, Dept Human Dev & Family Studies, University Pk, PA 16802 USA
[2] Univ New Mexico, Dept Psychol, Albuquerque, NM 87131 USA
[3] Univ Amsterdam, Dept Psychol, NL-1012 WX Amsterdam, Netherlands
[4] Syracuse Univ, Dept Psychol, Syracuse, NY 13244 USA
基金
美国国家科学基金会;
关键词
catastrophe; differential equation; mixture structural equation models; regime switching; dynamic; MAXIMUM-LIKELIHOOD; ALCOHOL-USE; EM; TRANSITIONS; CRITERION; VARIABLES; DRINKING; RELAPSE; NUMBER; SCALE;
D O I
10.1037/a0038962
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Catastrophe theory (Thom, 1972, 1993) is the study of the many ways in which continuous changes in a system's parameters can result in discontinuous changes in 1 or several outcome variables of interest. Catastrophe theory-inspired models have been used to represent a variety of change phenomena in the realm of social and behavioral sciences. Despite their promise, widespread applications of catastrophe models have been impeded, in part, by difficulties in performing model fitting and model comparison procedures. We propose a new modeling framework for testing 1 kind of catastrophe model-the cusp catastrophe model-as a mixture structural equation model (MSEM) when cross-sectional data are available; or alternatively, as an MSEM with regime-switching (MSEM-RS) when longitudinal panel data are available. The proposed models and the advantages offered by this alternative modeling framework are illustrated using 2 empirical examples and a simulation study.
引用
收藏
页码:142 / 164
页数:23
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