This chapter serves as a guide for the practical application of confirmatory factor analysis (CFA) in a longitudinal context (longitudinal confirmatory factor analysis, LCFA) and how a LCFA can be extended to a second-order growth curve model known as a curve-of-factors model, or CFM. The chapter provides a practical guide on how to: (1) incorporate autocorrelations, (2) impose factor invariance over time, and (3) extend a LCFA to a second-order growth curve (a CFM) using Mplus statistical software. Steps 1, 2, and 3 refer to the confirmatory factor model (LCFA) with first-order, or primary, latent factors, which represent the measurement model of a CFM. Step 3 addresses the estimation of a second-order latent growth curve model by adding secondary latent growth factors to a LCFA. This chapter also explains different scale setting approaches for the measurement model and their implication for second-order growth curve modeling. Finally, guidance is provided for incorporating time-invariant and time-varying covariates into a CFM to test various hypotheses related to antecedents and outcomes of change in a global latent factor.