R中的Cox比例风险模型和时间相关的Cox模型

Question

I have this survival data that describes the mortality rate of three types of services (saloon, restaurant and express)over a ten year time study.

The data contains three variables: service type (1=saloon, 2=restaurant, and 3=express), years (an integer from 1 to 11, where 11 means greater than 10 years) and censor.

I have two questions:

1) I have fitted the Cox proportional hazard model, but what are the ways to check the proportional hazard assumption. That is we assume the hazard ratio of each individual and the baseline hazard is independent of time.

2) How to fit a time dependent Cox model in R?

Here are my code:

   #Cox Proportional Hazards
   cox <- coxph(Surv(Years, Censor) ~ data$`Service Type` )
   summary(cox)

Answer 1

The cox.zph function in pkg survival checks for proportionality. Do note that using 'Service Type" as a column name provides programming hassles that one can be easily avoid by allowing periods to be substituted for spaces as is the default action with read.table:

data <- read.table(url("http://www.stat.ufl.edu/~winner/data/bizmort.dat"), col.names=c("Service Type","Years",  "Censor")
# Also note that the censoring indicatior is reversed so will use 1-Censor
require(survival)

cox <- coxph(Surv(Years, 1-Censor) ~ factor(Service.Type), data=data )
# The test fro proportionality:

> cox.zph(cox)
                         rho chisq     p
factor(Service.Type)2 0.0306  0.98 0.322
factor(Service.Type)3 0.0429  1.91 0.167
GLOBAL                    NA  2.33 0.312