standardize.prodlim: Standardize absolute risks

Description Usage Arguments Details Author(s) Examples

Description

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

Usage

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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 <[email protected]>

Examples

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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 June 21, 2019, 6:37 p.m.