Ben Sabath June 16, 2021
This directory contains code covering the creation of the data set used for analysis in the Health Effects Institute Final Report "Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Pollution: Implementation of Causal Inference Methods."
The directory Confounders contains the process by which the zip code
level demographic data, smoking and BMI data, and weather data are
acquired and prepared for use. Exposures describes the preparation of
the PM2.5 data. Please note that we are unable to provide the code and
workflow, as our exposure data is provided by our collaborators.
However, the PM2.5 exposure data we used is available for download
here.
HealthOutcomes contains the code used to select data from the Medicare
Beneficiary Summary Files. Finally, MergedData contains the process by
which all these data sources are combined and cleaned in order to be
analyzed by the code in StatisticalAnalysis.
We have included as much data as we are allowed to share and can feasibly include in a github repo (some files are too large to share). Where we are unable to share data, we have provided instructions on how to acquire the source data and prepare it for use with the data pipelines.
The directories can be read in any order; however, reading in the following order reflects how data flows in the pipeline.
- Confounders Overview of non health, non
pm2.5 data used.
- Census Data (All data needed provided)
- Smoking and BMI (Some external data Downloads needed)
- Temperature and Humidity (Some external data downloads needed)
- PM2.5 Data (Not fully reproducible)
- Medicare Mortality Data (Additional Data Acquisition Needed)
- Merging Process
- Statistical Analysis