Nonlinear Growth Models in Mplus and SAS

被引：136

作者：

Grimm, Kevin J. ^{[1
]}

Ram, Nilam ^{[2
,3
]}

机构：

[1] Univ Calif Davis, Dept Psychol, Davis, CA 95616 USA

[2] Penn State Univ, University Pk, PA 16802 USA

[3] Max Planck Inst Human Dev, Berlin, Germany

来源：

STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL | 2009年 / 16卷 / 04期

基金：

美国国家科学基金会;

关键词：

LONGITUDINAL STRUCTURAL-ANALYSES; MIXED-EFFECTS MODELS; LATENT CURVE MODELS; INDIVIDUAL-DIFFERENCES; MULTILEVEL MODELS;

D O I：

10.1080/10705510903206055

中图分类号：

O1 [数学];

学科分类号：

070101 [基础数学];

摘要：

Nonlinear growth curves or growth curves that follow a specified nonlinear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this article we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the nonlinear mixed-effects modeling procedure NLMIXED in SAS. Using longitudinal achievement data, collected as part of a study examining the effects of preschool instruction on academic gain, we illustrate the procedures for fitting growth models of logistic, Gompertz, and Richards functions. Brief notes regarding the practical benefits, limitations, and choices faced in the fitting and estimation of such models are included.

引用

页码：676 / 701

页数：26

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