Covariance Pattern Mixture Modeling Identifies Two Openness Trajectory Classes Among Older Adults

Covariance Pattern Mixture Models (CPMMs) identify heterogeneous populations within a single sample by modeling residual covariance matrices to account for non-independence of observations. We utilize CPMMs to examine changes in openness to experience in large, longitudinal sample of older adults. Two latent classes with compound symmetric residual correlation structure emerged.