When the Include Missing option is selected, does Latent Gold do some kind of imputation?
A. No, imputation is not necessary. Classification with missing values works exactly the same as classification without missing values. It is simply based on the variables that are observed for the case concerned. There is no imputation of missing values for indicators. One of the nice things about LC analysis is that imputation is not necessary. In the User’s Guide, we give the general form of the density with missing values. The crucial thing is the delta, which is 0 if an indicator is missing. If that occurs the term cancels (it is equal to 1 irrespective of the value of y). Thus with 4 indicators y1, y2, y3, and y4, two clusters and y2 missing P(x|y1,y3,y4) = P(x) P(y1|x) P(y3|x) P(y4|x) / P(y1,y3,y4) where P(y1,y3,y4) = P(1) P(y1|1) P(y3|1) P(y4|1) + P(2) P(y1|2) P(y3|2) P(y4|2) Return to List of Questions Q. How are Latent Class (LC) clustering techniques related to Fuzzy Clustering Techniques A. In fuzzy clustering, a case has grades of membership which are the “parameters” to b
