Title

groupsbrm -- Using Predictions and
Marginal Effects to Compare Groups in Regression Models
for Binary Outcomes. 23Oct2018

Overview

The groupsbrm package provides do-files to reproduce the analyses in:

Scott Long and Sarah Mustillo (2108)
Using Predictions and Marginal Effects to Compare Groups
in Regression Models for Binary Outcomes.
Sociological Methods and Research.

Obtaining the dataset

HRS does not allow us to distribute our analysis dataset groupcompare-hrs1.dta,
but you can download it from their site. As of 2018-10-23, you could find
our dataset with the following instructions, but not the HRS site may have
changed the steps.

1. Register at the University of Michigan/HRS data download site
at https://ssl.isr.umich.edu/hrs/login2.php and log in.

2. Select Data Downloads at the bottom of the page. Then,
on right side, go to section Researcher Contributions.

3. Click on the link for
"Using predictions and marginal effects to compare groups in regression models for binary outcomes (v.1.0)"
near the bottom of the list to download LongMustillo-datasubmission.zip.

4. Unzip the file to obtain (a) groupcompare-hrs1.dta with the analysis data;
(b) groupcompare-hrs1.txt describing the dataset; (c)
groupcompare-hrs-supportv1.do with commands we used to create the dataset.

Reproducing the results from our paper

1. Verify that you have installed the spost13_ado package.
To do this, run spex logit. If you receive an error,
run search spost13_ado and follow the instructions.

2. Place groupcompare-hrs1.dta along with the
do-files installed with the groupsbrm package:
long-mustillo-groups-descriptives.do,
long-mustillo-groups-goodhlth.do,
long-mustillo-groups-diabetes.do,
and
long-mustillo-groups-diabetes-allisontests.do
in your working directory.
The results from the do-files could
differ from those in our paper if you have different releases
of the HRS datasets.

Acknowledgments

Analysis uses SPost 13:
J. Scott Long & Jeremy Freese. 2014.
Regression Models for Categorical Dependent Variables Using Stata, 3rd Edition.
College Station, TX: Stata Press