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Hancock, Gregory R. – Structural Equation Modeling, 1999
Proposes an analog to the Scheffe test (H. Scheffe, 1953) to be applied to the exploratory model-modification scenario. The method is a sequential finite-intersection multiple-comparison procedure that controls the Type I error rate to a desired alpha level across all possible post hoc model modifications. (SLD)
Descriptors: Structural Equation Models
Peer reviewed Peer reviewed
Hancock, Gregory R.; Nevitt, Jonathan – Structural Equation Modeling, 1999
Explains why, when one is using a bootstrapping approach for generating empirical standard errors for parameters of interest, the researchers must choose to fix an indicator path rather than the latent variable variance for the empirical standard errors to be generated properly. (SLD)
Descriptors: Error of Measurement, Identification, Structural Equation Models
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Hancock, Gregory R.; Kuo, Wen-Ling; Lawrence, Frank R. – Structural Equation Modeling, 2001
Using higher order factor models, this article illustrates latent curve analysis for the purpose of modeling longitudinal change directly in a latent construct. Provides examples with simultaneous estimation of covariance and mean structures for a single-group and two-group structure. (SLD)
Descriptors: Analysis of Covariance, Factor Analysis, Mathematical Models
Peer reviewed Peer reviewed
Nevitt, Jonathan; Hancock, Gregory R. – Structural Equation Modeling, 2001
Evaluated the bootstrap method under varying conditions of nonnormality, sample size, model specification, and number of bootstrap samples drawn from the resampling space. Results for the bootstrap suggest the resampling-based method may be conservative in its control over model rejections, thus having an impact on the statistical power associated…
Descriptors: Estimation (Mathematics), Power (Statistics), Sample Size, Structural Equation Models