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How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction
2011 Aug 17
4
How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction
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> age_Q <- cut(x17.df$age, right=TRUE, breaks=c(-Inf, 66, 72, 76, Inf),
labels=c("53-66", "67-72", "73-76", "77-85"))
> table(age_Q)
age_Q
53-66 67-72 73-76 77-85
26 27 25 26
Then, I used mjca of ca pacakge for MCA.
> mjca1 <- mjca(mydata.df[, c("age_Q","sex","symptom", "HT", "DM",
"IHD","smoking","DL", "Statin")])
> summary(mjca1)
Principal inertias (eigenvalues):
dim value % cum% scree plot
1 0.0095...