ccwc {Epi}R Documentation

Generate a nested case-control study

Description

Given the basic outcome variables for a cohort study: the time of entry to the cohort, the time of exit and the reason for exit ("failure" or "censoring"), this function computes risk sets and generates a matched case-control study in which each case is compared with a set of controls randomly sampled from the appropriate risk set. Other variables may be matched when selecting controls.

Usage

ccwc(entry=0, exit, fail, origin=0, controls=1, match=list(), include=list(), data=NULL, silent=F)

Arguments

entry Time of entry to follow-up
exit Time of exit from follow-up
fail Status on exit (1=Fail, 0=Censored)
origin Origin of analysis time scale
controls The number of controls to be selected for each case
match List of categorical variables on which to match cases and controls
include List of other variables to be carried across into the case-control study
data Data frame in which to look for input variables
silent If False, echos a . to the screen for each case-control set created; otherwise produces no output.

Value

The case-control study, as a dataframe containing:

Set case-control set number
Map row number of record in input dataframe
Time failure time of the case in this set
Fail failure status (1=case, 0=control)

These are followed by the matching variables, and finally by the variables in the include list

Author(s)

David Clayton

References

Clayton and Hills, Statistical Models in Epidemiology, Oxford University Press, Oxford:1993.

See Also

Lexis

Examples

#
# For the diet and heart dataset, create a nested case-control study
# using the age scale and matching on job
#
data(diet)
dietcc <- ccwc(doe, dox, chd, origin=dob, controls=2, data=diet,
               include=energy, match=job)

[Package Epi version 1.0.12 Index]