[R] Validation / Training - test data

Dear List, I have developed two models i want to use to predict a response, one with a binary response and one with a ordinal response. My original plan was to divide the data into test (300 entries) and training (1000 entries) and check the power of the model by looking at the % correct

Re: [R] Validation / Training - test data

Split sample validation is highly unstable with your sample size. The rms package can help with bootstrapping or cross-validation, assuming you have all modeling steps repreated for each resample. Frank - Frank Harrell Department of Biostatistics, Vanderbilt University -- View this

Re: [R] Validation / Training - test data

Thanks for this, I had used validate(model0, method=boot,B=200) To get a index.corrected Brier score, However i am also wanting to bootstrap the predicted probabilities output from predict(model1, type = response) to get a idea of confidence, or am i best just using se.fit = TRUE and

Re: [R] Validation / Training - test data

It all depends on the ultimate use of the results. Frank - Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Validation-Training-test-data-tp2718523p2719370.html Sent from the R help mailing list archive at