The article discusses how latent variables can be used in statistical analysis to capture various concepts like random effects, missing data, and sources of variation. It goes beyond traditional uses in psychometrics to include models like factor models, growth curve models, and multilevel models. The researchers argue for integrating statistical and psychometric modeling ideas to create a unifying framework for different analysis types.