Measurement Invariance across Groups in Latent Growth Modeling
Document Type
Article
Publication Date
2014
Keywords
factorial invariance, latent growth model, measurement invariance, multiple group analysis, second-order latent growth model
Digital Object Identifier (DOI)
http://dx.doi.org/10.1080/10705511.2014.915374
Abstract
This Monte Carlo study investigated the impacts of measurement noninvariance across groups on major parameter estimates in latent growth modeling when researchers test group differences in initial status and latent growth. The average initial status and latent growth and the group effects on initial status and latent growth were investigated in terms of Type I error and bias. The location and magnitude of noninvariance across groups was related to the location and magnitude of bias and Type I error in the parameter estimates. That is, noninvariance in factor loadings and intercepts was associated with the Type I error inflation and bias in the parameter estimates of the slope factor (or latent growth) and the intercept factor (or initial status), respectively. As noninvariance became large, the degree of Type I error and bias also increased. Other findings and implications on future studies were discussed.
Rights Information
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Structural Equation Modeling, v. 21, issue 3, p. 408-424.
Scholar Commons Citation
Kim, Eun Sook and Willson, Victor L., "Measurement Invariance across Groups in Latent Growth Modeling" (2014). Educational Measurement and Research Faculty Publications. 1.
https://digitalcommons.usf.edu/edq_facpub/1
