threg (version 1.0.3)

hr: Hazard ratio calculation for threshold regression model

Description

This function can be used to estimate hazard ratios at selected time points for specified scenarios (based on given categories or value settings of covariates).

Usage

hr(object,var,timevalue,scenario) 
"hr"(object,var,timevalue,scenario)

Arguments

object

a threg object.

var

specifies the categorical variable for the calculation of hazard ratios. Such categorical variable must be a factor variable that has been used in threg() that returns the threg object.

timevalue

specifies a value of time at which the hazard ratios are calculated. A vector is allowed.

scenario

specifies a scenario where the hazard ratios are calculated.

Examples

#load the data "lkr"
data("lkr")

#Transform the "treatment2" variable into factor variable "f.treatment2" .
lkr$f.treatment2=factor(lkr$treatment2)

#fit the threshold regression model on the factor variable "f.treatment2", 
fit<-threg(Surv(weeks, relapse)~ f.treatment2|f.treatment2,data = lkr)
fit

#calculate the hazard ratio of the drug B group v.s. the standard group at 
#week 5 (this hazard ratio is calculated as 2.08)
hr.threg(fit,var=f.treatment2,timevalue=5)

#calculate the hazard ratio of the drug B group v.s. the standard group at 
#week 20 (this hazard ratio is calculated as 0.12)
hr.threg(fit,var=f.treatment2,timevalue=20)

#As a comparison, fit the Cox proportion hazards model on "f.treatment2", 
#and the Cox model gives a constant hazard ratio, 0.73.
summary(coxph(Surv(weeks, relapse) ~ f.treatment2, data = lkr))



#load the data "bmt"
data("bmt")

#Transform the "group" and "fab" variables into factor variables 
#"f.group" and "f.fab".
bmt$f.group=factor(bmt$group)
bmt$f.fab=factor(bmt$fab)

#fit a threshold regression model on the "bmt" dataset, by using "recipient_age" and 
#"f.fab" as the predictors for ln(y0), and "f.group" and "f.fab" as predictors for mu.
fit<-threg(Surv(time, indicator)~ recipient_age+f.fab|f.group+f.fab, data = bmt)
fit

#Calculate the hazard ratio for 
#"f.group" for the specified scenario that "the patient age is 18 years old and 
#the FAB classification is 0", at the time ``500 days''.
hr.threg(fit,var=f.group,timevalue=500,scenario=recipient_age(18)+f.fab1(0))