Re: [R] How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction

2011-08-20 Thread khosoda
Dear Mark, Thank you very much for your advice. I will try it. I really appreciate your all kind advice. Thanks a lot again. Best regards, Kohkichi (11/08/19 22:28), Mark Difford wrote: On Aug 19, 2011 khosoda wrote: I used x10.homals4$objscores[, 1] as a predictor for logistic

Re: [R] How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction

2011-08-19 Thread khosoda
Dear Mark, Thank you very much for your kind advice. Actually, I already performed penalized logistic regression by pentrace and lrm in package rms. The reason why I wanted to reduce dimensionality of those 9 variables was that these variables were not so important according to the subject

Re: [R] How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction

2011-08-19 Thread Mark Difford
On Aug 19, 2011 khosoda wrote: I used x10.homals4$objscores[, 1] as a predictor for logistic regression as in the same way as PC1 in PCA. Am I going the right way? Hi Kohkichi, Yes, but maybe explore the sets= argument (set Response as the target variable and the others as the predictor

Re: [R] How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction

2011-08-18 Thread Daniel Malter
Pooling nominal with numeric variables and running pca on them sounds like conceptual nonsense to me. You use PCA to reduce the dimensionality of the data if the data are numeric. For categorical data analysis, you should use latent class analysis or something along those lines. The fact that

Re: [R] How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction

2011-08-18 Thread khosoda
Dear Daniel, Thank you for your mail. Your comment is exactly what I was worried about. I konw very little about latent class analysis. So, I would like to use multiple correspondence analysis (MCA) for data redution. Besides, the first plane of the MCA captured 43% of the variance. Do you

Re: [R] How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction

2011-08-18 Thread Mark Difford
On Aug 17, 2011 khosoda wrote: 1. Is it O.K. to perform PCA for data consisting of 1 continuous variable and 8 binary variables? 2. Is it O.K to perform transformation of age from continuous variable to factor variable for MCA? 3. Is mjca1$rowcoord[, 1] the correct values as a predictor

Re: [R] How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction

2011-08-18 Thread Mark Difford
On Aug 18, 2011; Daniel Malter wrote: Pooling nominal with numeric variables and running pca on them sounds like conceptual nonsense to me. Hi Daniel, This is not true. There are methods that are specifically designed to do a PCA-type analysis on mixed categorical and continuous variables,

Re: [R] How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction

2011-08-18 Thread khosoda
Dear Mark, Thank you very much for your mail. This is what I really wanted! I tried dudi.mix in ade4 package. ade4plaque.df - x18.df[c(age, sex, symptom, HT, DM, IHD, smoking, DL, Statin)] head(ade4plaque.df) age sex symptom HT DM IHD smoking hyperlipidemia

[R] How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction

2011-08-17 Thread khosoda
Hi all, I'm trying to do model reduction for logistic regression. I have 13 predictor (4 continuous variables and 9 binary variables). Using subject matter knowledge, I selected 4 important variables. Regarding the rest 9 variables, I tried to perform data reduction by principal component