standardize.prodlim: Standardize absolute risks

In tagteam/heaven: Data Preparation Routines for Medical Registry Data

Standardize absolute risks

Description

Compute standardized absolute risks based on a stratified Kaplan-Meier or Aalen-Johansen estimate

Usage

standardize.prodlim(object, var1, var2, times, data, weights, ...)

Arguments

object	Object obtained with prodlim stratified with two categorical covariates.
var1	Name of one of the two categorical variables. The absolute risks are standardized within the levels of this variables to the distribution of the other categorical variable in the full data.
var2	Name of the other of the two categorical variables, i.e., the one on which the weights are based.
times	Compute absolute risks at these time points
data	Only if weights are not given. Data set in which to compute the weights for standardization as percentage in each of the levels of var2.
weights	A numeric vector of weights that sum to 1 and has length equal to the number of strata defined by var2. If omitted, weights are calculated using data.
...	not used

Details

Fit prodlim with two categorical covariates, say age and sex. Then standardize the absolute risk within each of the two gender to the age distribution in whole data set.

Author(s)

Thomas A. Gerds <[e-mail]>

Examples

library(survival)
library(prodlim)
library(data.table)
data(pbc)
d <- na.omit(pbc[,c("time","status","trt","age","sex")])
d$agegroup <- cut(d$age,breaks=c(0,40,50,60,100))
fit <- prodlim(Hist(time,status==1)~trt+agegroup,data=d)
standardize.prodlim(fit,var1="trt",var2="agegroup",data=d,times=1000)
standardize.prodlim(fit,var1="trt",var2="agegroup",data=d,times=c(1000,1500))

tagteam/heaven documentation built on Oct. 24, 2024, 7:40 p.m.