ccwc: Generate a nested case-control study

In Epi: Statistical Analysis in Epidemiology

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=FALSE )

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)

Epi documentation built on Oct. 1, 2024, 5:07 p.m.