Literature DB >> 23882134

Non-linear Growth Models in Mplus and SAS.

Kevin J Grimm1, Nilam Ram.   

Abstract

Non-linear growth curves or growth curves that follow a specified non-linear function in time enable researchers to model complex developmental patterns with parameters that are easily interpretable. In this paper we describe how a variety of sigmoid curves can be fit using the Mplus structural modeling program and the non-linear 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.

Entities:  

Year:  2009        PMID: 23882134      PMCID: PMC3717396          DOI: 10.1080/10705510903206055

Source DB:  PubMed          Journal:  Struct Equ Modeling        ISSN: 1070-5511            Impact factor:   6.125


  13 in total

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2.  Biological response curves.

Authors:  W W WESTERFELD
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Review 7.  Gompertzian growth and decay: a powerful descriptive tool for neuroscience.

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10.  Latent variable growth within behavior genetic models.

Authors:  J J McArdle
Journal:  Behav Genet       Date:  1986-01       Impact factor: 2.805

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  32 in total

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2.  Poisson Growth Mixture Modeling of Intensive Longitudinal Data: An Application to Smoking Cessation Behavior.

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Journal:  Struct Equ Modeling       Date:  2012-01       Impact factor: 6.125

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4.  Teacher's Corner: Latent Curve Models and Latent Change Score Models Estimated in R.

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5.  Identifying learning patterns of children at risk for Specific Reading Disability.

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6.  From science student to scientist: Predictors and outcomes of heterogeneous science identity trajectories in college.

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7.  Piecewise latent growth models: beyond modeling linear-linear processes.

Authors:  Jeffrey R Harring; Marian M Strazzeri; Shelley A Blozis
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8.  Science identity development trajectories in a gateway college chemistry course: Predictors and relations to achievement and STEM pursuit.

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9.  Sigmoidal mixed models for longitudinal data.

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10.  A Second-Order Conditionally Linear Mixed Effects Model With Observed and Latent Variable Covariates.

Authors:  Jeffrey R Harring; Nidhi Kohli; Rebecca D Silverman; Deborah L Speece
Journal:  Struct Equ Modeling       Date:  2012-01-23       Impact factor: 6.125

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