ABSTRACT
The previous chapter introduced a factor-of-curves model (FCM), which is a second-order growth curve model building on a parallel process model (PPM). The present chapter serves as a practical guide to estimating a factor-of-curves model (FCM) in a step-by-step manner. The chapter also discusses advantages of a FCM over a conventional latent growth curve model (LGCM). Detailed instructions for adding covariates (predictors and outcomes) to a FCM are provided using example models. We also discuss the estimation of a multiple-group FCM and a multivariate FCM. Lastly, the chapter demonstrates how a higher-order FCM can be built from a curve-of-factors model (CFM). For each model, figures, Mplus syntax, and outputs are presented.
