Confirmatory Latent Class Analysis
提出验证性潜在类别分析的操作框架，通过两个示例（双样本法和假设检验法）展示如何施加模型约束来检验理论假设，帮助研究者进行更严格的验证和复制。
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.