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...ich runs perfectly at least for fixed and random effects as well as for quantile regression adding dummies of states and years just like fixed effects). Any help would be highly appreciate Thanks Dimitris ###################################### The code that I use before using the link is: data$lex2<-data$lex^2 data$lex3<-data$lex^3 data$constant<-rep(1,times=length(data$lex)) X<-cbind(data$lex, data$lex2, data$lex3, data$constant) y<-c(data$ban) s<-c(data$state) -- View this message in context: http://www.nabble.com/Quantile-Regression-for-Longitudinal-Data.-Warning-m...

...: [[M2]] = metadata !{i32 {{[0-9]*}}, null, metadata [[CTXT]], i32 {{[0-9]*}}} ; [ DW_TAG_imported_module ] +// CHECK: [[M3]] = metadata !{i32 {{[0-9]*}}, null, metadata [[CTXT]], i32 15, metadata !"E"} ; [ DW_TAG_imported_module ] // CHECK: [[M4]] = metadata !{i32 {{[0-9]*}}, metadata [[LEX2:![0-9]*]], metadata [[NS]], i32 19} ; [ DW_TAG_imported_module ] // CHECK: [[LEX2]] = metadata !{i32 {{[0-9]*}}, metadata [[FILE2]], metadata [[LEX1:![0-9]+]], i32 {{[0-9]*}}, i32 0, i32 {{.*}}} ; [ DW_TAG_lexical_block ] // CHECK: [[LEX1]] = metadata !{i32 {{[0-9]*}}, metadata [[FILE2]], metadat...

Dear R-users, Is there a function in R that classifies data in more than 2 groups using logistic regression/classification? I want to compare the c-indices of earlier research (lrm, binary response variables) with new c-indices obtained from 'multiple' (more response variables) logistic regression. Best regards, Stephanie Delalieux Department Biosystems M?-BIORES Group of Geomatics