Hi List, I'm following on the discussions regarding the use of exploratory factor analysis with binary data, from nabble:
http://www.nabble.com/PCA--for-Binary-data-to11050371.html#a11092127 and i tried using FactorMineR package but unfortunately i have trouble understanding what are the types of the variables which AFDM is suitable for? I guessed from that example in ?AFDM that "n" is for categorical variables and "s" for numerical variables. Am I right? Could this type of factorial analysis give also the factor scores? How? My code (I'm using only binary variables) a<-c(sample(0:1, 10, replace=T)) b<-c(sample(0:1, 10, replace=T)) c<-c(sample(0:1, 10, replace=T)) d<-c(sample(0:1, 10, replace=T)) q<-t(rbind(a,b,c,d) ) q<-as.data.frame(q) AFDM(q, type=c("s", "s", "s", "s"))$eig #when the variables are treated as numerical q$a<-as.factor(q$a) q$b<-as.factor(q$b) q$c<-as.factor(q$c) q$d<-as.factor(q$d) q<-data.frame(q) AFDM(q, type=c("n", "n", "n", "n"))$eig #when the variables are treated as categorical The results are identical! Should it be ok? And if so how can i get the factor scores? Thank you and have a great day ahead! --------------------------------- [[elided Yahoo spam]] [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
