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Spring 2009 Featured Article |
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 Spring 2009:
Coffman, D. L. (2008). Model error in covariance structure models: Some implications for power and Type I error. Methodology, 4(4), 159-167.
Abstract: This study investigated the degree to which violation of the parameter drift assumption affects the Type I error rate for the test of close fit and the power analysis procedures proposed by MacCallum et al. (1996) for both the test of close fit and the test of exact fit. The parameter drift assumption states that as sample size increases both sampling error and model error (i.e., the degree to which the model is an approximation in the population) decrease. Model error was introduced using a procedure proposed by Cudeck and Browne (1992). The empirical power for both the test of close fit, in which the null hypothesis specifies that the root mean square error of approximation (RMSEA) I error rate under violations of the assumption. |
