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...the linear predictor of the Cox model. I have used Harrell's c index for censored data (rcorr.cens) as a measure of discrimination and have constructed smoothed calibration plots. I would like to include some measures of overall model performance, such as the censored Brier score and Royston/Sauerbrei's D statistic (Stat Med 2004). With this in mind, I have 3 questions: 1) Can the "sbrier" function of the "ipred" library be used to calculate the censored Brier score for a specific time point given known predictions for that timepoint? library(ipred) data <- read.c...

Hi, I am using logistic regression to classify a binary psychometric data. using glm() and then predict.glm() i got the predicted odds ratio of the testing data. Next i am going to plot ROC curve for the analysis of my study. Now what i will do: 1. first select a cut-off (say 0.4) and classify the output of predict.glm() into {0,1} segment and then use it to draw ROC curve using ROCR package

I am new to R, and I am trying to cut a continuous variable BMI into different categories and can't figure out how to use it. I would like to cut it into four groups: <20, 20-25, 25-30 and >= 30. I am having difficulty figuring the code for <20 and >=30? Please help. Thank you. -- View this message in context:

I am trying to create a frequency distribution and I am a bit confused. Here are the commands I have entered: > data <- read.csv(file="40609_sortedfinal.csv",head=TRUE,sep=",") > NumberOfActionsByStatus = data$STATUS > NumberOfActionsByUser = data$ETS_LOGIN > NumberOfBidOffer = data$BID_OFFER > NumberOfActionsByUser.freq = table(NumberOfActionsByUser) >