Category: Office Hours Videos

It is critical for researchers in the behavioral, health, and social sciences to have a full understanding of the linear regression model. Not only is…

In a prior episode of Office Hours, Patrick discussed predicting growth by time-invariant covariates (TICs), predictors for which the numerical values are constant over time.…

Once an optimal model of linear or nonlinear change has been established, it is often of interest to try to predict individual differences in change…

In this installment to our series of Office Hour videos on growth curve modeling, Patrick describes how to model nonlinear trajectories. Although the most basic…

Although latent class analysis (LCA) and latent profile analysis (LPA) were developed decades ago, these models have gained increasing recent prominence as tools for understanding…

In a prior episode of Office Hours, Patrick explored “Growth modeling in a multilevel modeling framework.” In the current episode he discusses how growth models…

In an earlier episode of Office Hours, Patrick addressed the question, “What is growth curve modeling?” In this episode he explores how a growth curve…

Whether estimating growth models in a structural equation or multilevel modeling framework, the researcher must choose how to numerically code the passage of time. In…

In this edition of CBA Office Hours, Dan discusses some of the principal advantages of the structural equation model (SEM) relative to more traditional data…