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Factor Analysis - Harvard University

Factor Analysis Qian-Li Xue Biostatistics Program Harvard Catalyst | The Harvard Clinical & Translational Science Center Short course, October 27, 2016. 1. Well-used latent variable models Latent Observed variable scale variable scale Continuous Discrete Continuous Factor Discrete FA. Analysis IRT (item response). LISREL. Discrete Latent profile Latent class Growth mixture Analysis , regression General software: MPlus, Latent Gold, WinBugs (Bayesian), NLMIXED (SAS). Objectives What is Factor Analysis ? What do we need Factor Analysis for? What are the modeling assumptions? How to specify, fit, and interpret Factor models? What is the difference between exploratory and confirmatory Factor Analysis ? What is and how to assess model identifiability?

Factor Analysis Qian-Li Xue Biostatistics Program Harvard Catalyst | The Harvard Clinical & Translational Science Center Short course, October 27, 2016 1 . Well-used latent variable models Latent variable ... F is independent of δ ...

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