Hi,
These are materials for logistic regression course II: Conditional logistic regression, the academic year 2019 (the calendar year 2020). This year I use R version 3.6.2 and the regression outputs are the same as that produced from the previous version of R.
Conditional logistic regression requires library survival that already exists in your R library folder. Just call
library(survival) or require
(survival) and you are ready to use
clogit function.
agechd.dta
cca-match.dta
The module can be downloaded here.
logistic1702-2.pdf
The required modules for this course are
ice and
epid which can be installed into R by manually installing the two packages, "
ice_3.4.0.1.zip" and "
epid_3.4.0.1.zip".
In this session, we are going to use multilevel logistic regression (
glmer) in dealing with data stratified by age group as if the stratification is a matching condition. This method
is recently used by some authors. Then we need another package from CRAN called "lme4". You can install the package by typing the following line on your R console.
install.packages
("lme4")
(Since the package is installed from CRAN or its mirror, a
repos argument is not required.)
Finally, you can follow my R script file below. Don't forget to change the working directory to yours.
conditional2.R
Additional reading:
The article "Medication risk factors associated with healthcare-associated Clostridium difficile infection: a multilevel model case–control study among 64 US academic medical
centres" shows how to use multilevel logistic regression so that the effect of the variables at the
contexual level can be identified. This method can be used to handle the matched analysis of a case-control study as well.
J. Antimicrob. Chemother.-2014-Pakyz-1127-31.pdf