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Testing differences between nested covariance structure models: Power analysis and null hypotheses
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DOI：10.1037/1082-989X.11.1.19.png)
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For comparing nested covariance structure models, the standard procedure is the likelihood ratio test of the difference in fit, where the null hypothesis is that the models fit identically in the population. A procedure for determining statistical power of this test is presented where effect size is based on a specified difference in overall fit of the models. A modification of the standard null hypothesis of zero difference in fit is proposed allowing for testing an interval hypothesis that the difference in fit between models is small, rather than zero. These developments are combined yielding a procedure for estimating power of a test of a null hypothesis of small difference in fit versus an alternative hypothesis of larger difference.
Keyword:
power analysis
structural equation modeling
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Power analysis and determination of sample size for covariance structure modeling协方差结构建模的功率分析和样本量的确定
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分享收藏ASYMPTOTIC CHI-SQUARE TESTS FOR A LARGE CLASS OF FACTOR-ANALYSIS MODELS.png)
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ANNALS OF STATISTICSIF3.7
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