Literature DB >> 30627936

Creating Misspecified Models in Moment Structure Analysis.

Keke Lai1.   

Abstract

To understand how SEM methods perform in practice where models always have misfit, simulation studies often involve incorrect models. To create a wrong model, traditionally one specifies a perfect model first and then removes some paths. This approach becomes difficult or even impossible to implement in moment structure analysis and fails to control the amounts of misfit separately and precisely for the mean and covariance parts. Most importantly, this approach assumes a perfect model exists and wrong models can eventually be made perfect, whereas in practice models are all implausible if taken literally and at best provide approximations of the real world. To improve the traditional approach, we propose a more realistic and flexible way to create model misfit for multiple group moment structure analysis. Given (a) the model [Formula: see text] and [Formula: see text], (b) population model parameters [Formula: see text], and (c) [Formula: see text] and [Formula: see text] specified by the researcher, our method creates [Formula: see text] and [Formula: see text] to simultaneously satisfy (a) [Formula: see text], (b) the mean structure's misfit equals [Formula: see text], and (c) the covariance structure's misfit equals [Formula: see text].

Keywords:  Monte Carlo experiments; model misspecification; moment structure analysis; multiple group analysis

Year:  2019        PMID: 30627936     DOI: 10.1007/s11336-018-09655-0

Source DB:  PubMed          Journal:  Psychometrika        ISSN: 0033-3123            Impact factor:   2.500


  5 in total

1.  Model selection in covariance structures analysis and the "problem" of sample size: a clarification.

Authors:  R Cudeck; S J Henly
Journal:  Psychol Bull       Date:  1991-05       Impact factor: 17.737

2.  2001 Presidential Address: Working with Imperfect Models.

Authors:  Robert C MacCallum
Journal:  Multivariate Behav Res       Date:  2003-01-01       Impact factor: 5.923

3.  Sample Size in Factor Analysis: The Role of Model Error.

Authors:  R C MacCallum; K F Widaman; K J Preacher; S Hong
Journal:  Multivariate Behav Res       Date:  2001-10-01       Impact factor: 5.923

4.  Quantifying Adventitious Error in a Covariance Structure as a Random Effect.

Authors:  Hao Wu; Michael W Browne
Journal:  Psychometrika       Date:  2015-03-27       Impact factor: 2.500

5.  The Problem with Having Two Watches: Assessment of Fit When RMSEA and CFI Disagree.

Authors:  Keke Lai; Samuel B Green
Journal:  Multivariate Behav Res       Date:  2016-03-25       Impact factor: 5.923

  5 in total

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