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    Multinomial logistic regression Interpretation

    I'm trying to understand the result of the Odds Ratio library(nnet) model <- multinom(labs~GENDER+Education+Imp,data=mydata) GENDER = (Man, Woman) Education = (Primary, Secondary, University) Imp = (YES, NO) I have 300 participants in my study, I clustered them in 3 Clusters So in...
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    Compare different methods for classifying two datasets

    I'm not sure if this question is Applied Statistics, my apologies if it isn't. I have different implementations of different classification models (Discriminant Analsis, SVM, Neural Networks, Decision trees, etc) a total of 40 implementations and I need to compare them in two different sets...
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    Why not use Kaplan Meier?

    In the method described here R code implementation is provided the Kaplan-Meier estimator is initially estimated from data but then (from line 244) different distributions...