Transcription of Factor Analysis - Harvard University
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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 ?
Given all variables in standardized form, i.e. var(Y i)=var(F i)=1; AND oblique factors (i.e. cov(F 1,F 2)≠0) ! The interpretation of factor loadings: λ ij is no longer correlation between Y and F; it is direct effect of F on Y ! The calculation of communality of Yi (h i 2) is more complex 16
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