standardize.proportion: Standardize proportions and absolute risks to a given age...

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

Standardize proportions and absolute risks to a given age distribution

Description

Standardize proportions and absolute risks to a given age distribution

Usage

standardize.proportion(
  vars,
  agevar,
  byvar,
  data,
  ref = 2,
  formula,
  cause,
  times,
  level = 0.95,
  ...
)

Arguments

vars	Name vector of categorical variables
agevar	Name of categorical age variable
byvar	Name of categorical strata variable
data	Data set
ref	For categorical variable that are not factors the level for which we calculate the standardized proportion
formula	Passed to prodlim for calculation of absolute risks
cause	In case of competing risks the cause of interest
times	The time point(s) for evaluation of absolute risks
level	Confidence level
...	Not (yet) used

Details

Standardize proportions and absolute risks to a given age distribution

Value

Data table with standardized proportions and standardized absolute risks

Author(s)

Thomas A. Gerds <[e-mail]>

See Also

standardize.prodlim

Examples

library(riskRegression)
set.seed(84)
d <- riskRegression::sampleData(83)
d[,X1:=factor(X1,levels=c("0","1"),labels=c("0","1"))]
d[,X2:=factor(X2,levels=c("0","1"),labels=c("0","1"))]
d[,agegroups:=cut(X6,c(-Inf,40,60,Inf))]
standardize.proportion(vars=c("X1","X2"),agevar="agegroups",byvar="X4",data=d)

tagteam/heaven documentation built on March 24, 2024, 7:58 a.m.