How to create an index with only categorical variables (dichotomous, nominal and ordinal) only? I am currently conducting a study about the involvement of male in family planning. It is of interest to create an index for the involvement of male in FP. My variables were only categorical variables and mainly dichotomous variables. Is there anyone who is knowledgeable on creating index using logistic approach? or any suggestions for the creation of this index. Thanks so much
 A: The general sequence for this kind of problem is:


*

*check your items actually scale together

*fit an IRT model to them

*confirm your model fits reasonably

*extract factor scores for cases


If you happen to be an R user then one can do 1. using the aisp function in the mokken package.  This looks at your items and tries to tell you how many (if any) separate scales there are among your items.  You can also compute Cronback alphas and other stats with this package.
If for 2. you want to fit an item response model -- I'm guessing this is what you mean by 'logistic approach' -- then you can use the grm function from the ltm package to fit a scale that has some mix of dichotomous or Likert items, and the factor.scores function to get scale scores for whatever subset of items you chose.  
More practical detail and pointers to the relevant theory is provided by the package vignette.  As it happens the example code all uses the built in data set WIRS which consists of 6 dichotomous items, so you can see how it works using that.
