Testing Measurement Invariance across Groups in Longitudinal Data: Multi-group Second-order Latent Growth Model
iterative likelihood ratio test, latent growth model, longitudinal data, multiple group analysis, measurement invariance, Monte Carlo simulation
In latent growth modeling measurement invariance across groups has received little attention. Considering that a group difference is commonly of interest in social science, a Monte Carlo study explored the performance of multi-group second-order latent growth modeling (MSLGM) in testing measurement invariance. True positive and false positive rates in detecting noninvariance across groups in addition to bias estimates of major MSLGM parameters were investigated. Simulation results support the suitability of MSLGM for measurement invariance testing when either forward or iterative likelihood ratio procedure is applied.
Citation / Publisher Attribution
Kim, E. S., & Willson, V. L. (2014). Testing measurement invariance across groups in longitudinal data: Multi-group second-order latent growth model. Structural Equation Modeling, 21(4), 566-576.
Scholar Commons Citation
Kim, Eun Sook and Willson, Victor L., "Testing Measurement Invariance across Groups in Longitudinal Data: Multi-group Second-order Latent Growth Model" (2014). Educational Measurement and Research Faculty Publications. Paper 2.