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2017 Nov 07
0
Survfit when new data has only 1 row of data
...btained from negative binomial, and zero-inflated negative binomial models for the same data (albeit in a different format) To my mind, and based on what I've read, the best way to do this is to use survfit. I want to make predictions for each individual, therefore, I have tried this code: trialnos <- unique(bdat5$trialno) prob0 <- function(ids,dataset,model,time){ probs <- rep(0,length(ids)) for(i in 1:length(ids)){ print(i) sdata <- subset(dataset,trialno==ids[i]) sfit <- survfit(model,newdata=sdata) probs[i] <-sum(summary(sfit,time)$surv) } return(probs)...
2008 Oct 28
3
Dose Profile
Hi Everyone, I have data in a long format e.g. there is one row per patient but each follow-up appointment is included in the row. So, a snippet of the data looks like this: TrialNo Drug Sex Rand Adate1 Date1 Dose1 Time1 Adate2 Date2 Dose2 Time2 B1001029 LTG M 15719 30/04/2003 15825 150 106 29/08/2003 15946 200 227 B1117003 LTG M 15734 30/04/2003 15825 200 91 03/09/2003 15951 250 217