范畴变量
多向拉希模型
潜在类模型
班级(哲学)
计算机科学
潜变量
计量经济学
数据科学
统计
数学
项目反应理论
机器学习
人工智能
心理测量学
标识
DOI:10.1016/j.sapharm.2016.11.011
摘要
The purpose of this paper is to provide a brief non-mathematical introduction to Latent Class Analysis (LCA) and a demonstration for researchers new to the analysis technique in pharmacy and pharmacy administration. LCA is a mathematical technique for examining relationships among observed variables when there may be collections of unobserved categorical variables. Traditionally, LCA focused on polytomous observed variables, but recent work has extended the types of data that can be utilized. Included in this introduction are basic guidelines for the information that should be part of a manuscript submitted for review. For the analysis, LatentGold is used, but I also include basic R code for running LCA and LC Regressions with the poLCA package.
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