Hi, I am estimating a latent growth model (three continuous variables), and have multiple time-invariant covariates predicting latent intercept and slope. How can I tell if adding the covariates significantly improved model fit, or if adding certain covariates to the slope, but not intercept is a better model. Thank you.
lotti posted on Wednesday, November 12, 2014 - 6:40 am
Dear Professor Muthen, I have a dual-process latent growth modeling. In univariate modeling, I found: (1) a significant linear increase in the first process over time (i.e., positive slope), and a linear decrease in the second process over time (i.e., negative slope). In the multivariate model, I specified a direct path from the slope and the intercept of the first (increasing) process to the slope of the second process. To my surprise, under this model the slope of the second process became positive. What does this mean? I'm very grateful for your help in understanding this.