PB HLTH 245 Lecture Notes - Lecture 6: Linear Combination, Factor Analysis, Correlation And Dependence

• School: Berkeley
• Department: Public Health
• Course: PB HLTH 245
• Professor: Lexin Li

Document Summary

Xi - mi = lift, t lezfa t - - - t el. Fi , fa common factors ( linear combination ) Same is the loading of variable i , xi on factor j . Fj: similar to pca analysis (percentage variance) ti is. Wvu , f) = opxm war- a- toni , ) Cov cx ) = e =l it 4 communality : the proportion of the variance of the ith variable. Xi that is contributed by m common factors ( common variance) the proportion of the variance of the specific variance ( uniqueness) n ith variable xi due to specific factor ei. In some cases , one work with correlation matrix rcf ) covariance matrix e instead of. X = out lf t e = me 277t ft e = out. { =l lt t 4 = ltt t lt t 4 = lk.