Description Usage Arguments Details Value Author(s) References Examples
The function calculates the effects of an exposure on a response, possibly stratified by a stratifying variable, and/or controlled for one or more confounding variables.
1 2 3 4 5 6 7 8 9 
response 
The 
exposure 
The 
match 
The variable which identifies the matched sets 
strata 
The 
control 
The 
base 
Baseline for the effects of a categorical exposure, default 1 
digits 
Number of significant digits for the effects, default 3 
alpha 
1  confidence level 
data 

Effects are calculated odds ratios. The function is a wrapper for clogit, from the survival package. The k1 effects for a categorical exposure with k levels are relative to a baseline which, by default, is the first level. The effect of a metric (quantitative) exposure is calculated per unit of exposure. The exposure variable can be numeric or a factor, but if it is an ordered factor the order will be ignored.
comp1 
Effects of exposure 
comp2 
Tests of significance 
Michael Hills
www.mhills.pwp.blueyonder.co.uk
1 2 3 4 5 6 7 8 9 10 11 12 13  library(Epi)
library(survival)
data(bdendo)
# d is the casecontrol variable, set is the matching variable.
# The variable est is a factor and refers to estrogen use (no,yes)
# The variable hyp is a factor with 2 levels and refers to hypertension (no, yes)
# effect of est on the odds of being a case
effx.match(d,exposure=est,match=set,data=bdendo)
# effect of est on the odds of being a case, stratified by hyp
effx.match(d,exposure=est,match=set,strata=hyp,data=bdendo)
# effect of est on the odds of being a case, controlled for hyp
effx.match(d,exposure=est,match=set,control=hyp,data=bdendo)

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