Most applications of person-centered methodologies have relied on data-driven approaches to class enumeration. As person-centered analyses grow in popularity within organizational research, confirmatory approaches may be sought to provide more stringent theoretical tests and to formalize replication efforts. Confirmatory latent class analysis (LCA) is achieved through placement of modeling constraints, yet there is variation in the types of potential constraints and a lack of standardization in evaluating model fit in published work. This article provides a comprehensive framework for operationalizing model constraints and demonstrates confirmatory LCA via two illustrations: (a) a dual sample approach ( n = 1,366 and n = 1,367 in exploratory and validation samples, respectively) and (b) confirmatory testing of a hypothesized latent class structure ( n = 1,483). We depict operationalization of threshold boundary and/or equality constraints under both illustrations to generate a confirmatory latent class structure, and explain methods of model evaluation and comparison to alternative models. The confirmatory model was well supported under the dual sample approach, and partially supported under the hypothesis-driven approach. We discuss decision making at various points of model estimation and end with future methodological developments.
Comprehensive framework for data-driven model form discovery of the closure laws in thermal-hydraulics codes
