Displaying 2 results from an estimated 2 matches for "predictprob".
2011 Dec 19
1
Calculating the probability of an event at time "t" from a Cox model fit
...=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 possible/ is there...
2012 Jan 17
1
Scoring using cox model: probability of survival before time t
...it_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 probabilities on scoring_data. Now, clo...