search for: peperr

...n, shape=1, scale=lambdaC) #censoring time time = pmin(T,C) #observed time is min of censored and true event = time==T # set to 1 if event is observed dataphr=data.frame(time,event,x1,x2) library(survival) fit_coxph <- coxph(Surv(time, event)~ x1 + x2 , method="breslow") library(peperr) predictProb.coxph(fit_coxph, Surv(dataphr$time, dataphr$event), dataphr, 0.003) # Using predictProb.coxph function, probability of event at time (t) is estimated for cox fit models, I want to estimate this probability on scoring dataset score_data as below with covariate x1 and x2. Is it possib...

Hi, I am attempting to evaluate the prediction error of a coxph model that was built after feature selection with glmnet. In the preprocessing stage I used na.omit (dataset) to remove NAs. I reconstructed all my factor variables into binary variables with dummies (using model.matrix) I then used glmnet lasso to fit a cox model and select the best performing features. Then I fit a coxph model

...rm(time,event,x1,x2) fit_coxph <- coxph(Surv(time, event)~ x1 + x2, data= train_sample, method="breslow") #Save model to some directory save(fit_coxph, file = file.path("C:/Desktop","fit_coxph.RData")) #I can get probabilities on train_sample as below: library(peperr) pred_train <- predictProb.coxph(fit_coxph, Surv(train_sample$time, train_sample$event), train_sample, 0.4) head(pred_train) # [,1] #[1,] 5.126281e-03 #[2,] 4.324882e-01 #[3,] 4.444506e-61 #[4,] 0.000000e+00 #[5,] 0.000000e+00 #[6,] 3.249947e-01 #In the same line, I need probabili...

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