> De : Pousset [mailto:[EMAIL PROTECTED] > Envoyi : mardi 4 juillet 2006 18:38 > @ : 'r-help@stat.math.ethz.ch' > Objet : Latent Class Analysis > > > > Hello everybody, > > > > I am working on latent class analysis and have already used the R > function > + lca ; (in the e1071 package). I ve got interesting results but I cant > simply find out the methodology used by this routine : > > 1) What kind of model is behind the routine (mixture model? If so, can you > choose among different kind of distributions such as normal, Poisson, > binomial) > > 2) What kind of algorithm is used (hierarchical methods? Relocation > methods?) > > 3) Which criterion allows determining the best model? > > In addition, I wonder if it is possible, with R software, to determine the > best number of class or do one have to fix it a priori. > > If one can help, thanks a lot, > > > > Maud > > INSERM U669, Cochin Hospital, Paris > > >
You can use package (available at R page) poLCA that has documentation describing what you want. Look also at http://dlinzer.bol.ucla.edu/poLCA/ As far as you know BIC, AIC (based on chi-sqr and G^2 statistics) and Cressie-Read allow you to choose the most appropriate model. Best, Robert ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html