Assessing Unobserved Within-Group Individual Differences

Task performance data distributions are often understood only after recognizing unobserved latent subpopulations. Finite mixture models offer an approach which can aid understanding, but often require difficult to justify decisions and model assumptions. With three or more individual repeated measures, a simple easily implemented cut-point approach often offers useful insights. Numerical examples are illustrative.