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!

  
       
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