Displaying 5 results from an estimated 5 matches for "intdaysuntilfvpo".
2008 Nov 29
0
Error in check(itp) : object does not represent a K sample problem with censored data
Hello,
I have two questions regarding a survival analysis I have been
working on. Below is the code to date.
The variables:
1) recidivism$intDaysUntilFVPO are the number of days before an
violent offence was committed - if no offence was committed than the
days between court hearing and end of data collection was recorded.
2) recidivism$intDaysUntilFNVPO are the number of days before a
nonviolent offence was committed - if no offence was committe...
2009 Mar 14
1
obtaining the values for the hazard function in a cox regression
...e correct command to obtain such values, to
better understand what is occurring in the log plots.
Below is the code that I have been using. Any assistance is appreciated,
regards
Bob
library(survival)
recidivismv <- read.csv("g://Chapsurv_v.csv",header=T)
cox.V <- coxph(Surv(intDaysUntilFVPO, Event_v) ~ intAgeAtMHCIndex +
PRE + group + MHC + strGender, data = recidivismv)
summary (cox.V)
# produces a log-log plot
mvfit <- survfit (Surv(recidivismv$intDaysUntilFVPO,
recidivismv$Event_v) ~ MHC, data = recidivismv)
neg.ll <- function(mvfit) -log(-log(mvfit))
library (Design)
su...
2009 Mar 16
0
hazard function in a Cox model
...to obtain the hazard function values. I am wanting to confirm
whether basehaz is the correct command to obtain such values, to
better understand what is occurring in the log plots.
--- end inclusion ----
The best tool for understanding what is happening is cox.zph.
cox.V <- coxph(Surv(intDaysUntilFVPO, Event_v) ~ intAgeAtMHCIndex +
PRE + group + MHC + strGender, data = recidivismv)
zpfit <- cox.zph(cox.V, transform='identity')
plot( zpfitp[1]) #plot for the first variable
plot( zpfitp[2]) #plot for the second
You will get a plot of beta(t) versus time,...
2009 Mar 28
1
stratified variables in a cox regression
...ot seen this approach used in R examples I have seen.
Below is my current code - is there a method to test whether the
stratified variables should be included in the final model at all?
library(survival)
recidivismv <- read.csv("g://Chapsurv_v.csv",header=T)
cox.V2 <- coxph(Surv(intDaysUntilFVPO, Event_v) ~ intAgeAtMHCIndex +
PRE + group + strata (MHC, strGender), data = recidivismv)
regards
Bob