Schreiber-Gregory, Deanna (2016). Latent Structure Analysis Procedures in SAS. PharmaSUG.
The current study looks at several ways to investigate latent variables in longitudinal surveys and their use in regression models. Three different analyses for latent variable discovery will be briefly reviewed and explored. The latent analysis procedures explored in this paper are PROC LCA, PROC LTA, PROC TRAJ, and PROC CALIS. The latent variables will then be included in separate regression models. The effect of the latent variables on the fit and use of the regression model compared to a similar model using observed data will be briefly reviewed. The data used for this study was obtained via the National Longitudinal Study of Adolescent Health, a study distributed and collected by Add Health. Data was analyzed using SAS® 9.4. This paper is intended for any level of SAS user. This paper is also written to an audience with a background in behavioral science and/or statistics.
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