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A framework for power analysis using a structural equation modelling procedure

Miles, Jeremy (2003) A framework for power analysis using a structural equation modelling procedure. BMC Medical Research Methodology. ISSN 1471-2288

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Abstract

BACKGROUND: This paper demonstrates how structural equation modelling (SEM) can be used as a tool to aid in carrying out power analyses. For many complex multivariate designs that are increasingly being employed, power analyses can be difficult to carry out, because the software available lacks sufficient flexibility. Satorra and Saris developed a method for estimating the power of the likelihood ratio test for structural equation models. Whilst the Satorra and Saris approach is familiar to researchers who use the structural equation modelling approach, it is less well known amongst other researchers. The SEM approach can be equivalent to other multivariate statistical tests, and therefore the Satorra and Saris approach to power analysis can be used. METHODS: The covariance matrix, along with a vector of means, relating to the alternative hypothesis is generated. This represents the hypothesised population effects. A model (representing the null hypothesis) is then tested in a structural equation model, using the population parameters as input. An analysis based on the chi-square of this model can provide estimates of the sample size required for different levels of power to reject the null hypothesis. CONCLUSIONS: The SEM based power analysis approach may prove useful for researchers designing research in the health and medical spheres.

Item Type: Article
Copyright, Publisher and Additional Information: © 2003 Miles; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
Institution: The University of York
Academic Units: The University of York > Health Sciences (York)
Depositing User: Repository Officer
Date Deposited: 28 Jul 2004
Last Modified: 15 Oct 2014 19:42
Published Version: http://dx.doi.org/10.1186/1471-2288-3-27
Status: Published
Refereed: Yes
Related URLs:
URI: http://eprints.whiterose.ac.uk/id/eprint/26

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