New SAS Software for LCA With Covariates

May 4, 2020:

blank LCA diagram: a latent variable represented by an oval and four arrows pointing towards manifest variables represented by rectangles

PROC LCA is our free add-on to SAS statistical software for estimating latent class models. We are pleased to announce the release of the LCA Covariates 3-Step SAS macro, which supplements PROC LCA’s functionality. The macro estimates the association between covariates and latent class membership using the approach of Bolck, Croon, and Hagenaars (2004), as adapted by Vermunt (2010) and Vermunt and Magidson (2015). It is a “three-step” (noninclusive) approach, which is a flexible and robust alternative to the “one-step” (inclusive) approach implemented via the COVARIATES statement in PROC LCA.

Note: This does not mean that models using the COVARIATES statement are invalid. It does mean that covariates will not affect estimation of the measurement model; when assumptions of the “one-step” approach are met, results using the new macro will be very similar to those with the COVARIATES statement.

Read more or download the macro.

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