Statistical points and pitfalls: growth modeling

Muthén BO, Curran PJ. General longitudinal modeling of individual differences in experimental designs: a latent variable framework for analysis and power estimation. Psychol Methods. 1997;2:371.

Muthén BO. Beyond SEM: general latent variable modeling. Behaviormetrika. 2002;29:81–117.

Willett JB, Sayer AG. Using covariance structure analysis to detect correlates and predictors of individual change over time. Psychol Bull. 1994;116:363.

Bryk AS, Raudenbush SW. Hierarchical linear models: applications and data analysis methods. SAGE; 1992.

Rabe-Hesketh S, Skrondal A. Multilevel and longitudinal modeling using Stata. STATA; 2008.

Xitao F, Xiaotao F. Power of latent growth modeling for detecting linear growth: number of measurements and comparison with other analytic approaches. J Exp Educ. 2005;73:121–39.

Muthén LK, Muthén BO. How to use a Monte Carlo study to decide on sample size and determine power. Struct Equ Model. 2002;9:599–620.

Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model Multidiscip J. 1999;6:1–55.

Bollen KA, Long JS. Testing structural equation models. Vol. 154. SAGE; 1993.

Curran PJ, Bauer DJ, Willoughby MT. Testing main effects and interactions in latent curve analysis. Psychol Methods. 2004;9:220.