An Analysis of Distress Tolerance as a Predictor of Early Treatment Dropout in a Residential Substance Abuse Treatment Facility
This repository contains the analysis conducted for the STOR 496 course at UNC-Chapel Hill. The project focuses on examining distress tolerance as a predictor of early treatment dropout in a residential substance abuse treatment facility, extending upon the methodologies employed in the original study by Daughters et al. (2005).
- Data Source: The study includes data from the Salvation Army Harbor Light residential substance abuse treatment center. This will not be included in the repository due to the sensitive nature of the data.
- Statistical Techniques: Utilizes descriptive statistics, correlation tests, Welch’s Two Sample t-tests, and Cox Proportional Hazards model for analysis.
- Software and Packages: Analysis conducted using R, with packages including
survivalfor Cox Proportional Hazards models.
- Ensure you have R installed on your system.
- Install the required R packages such as
install.packages("survival"). - Run the scripts in the file to reproduce the analysis
*Note that this will require access to the original data or your own data set which most will not possess
Special thanks to Dr. Daughters and Dr. Olvera-Cravioto, for their invaluable guidance throughout the course of this project.
Riley Harper - riley.harper@unc.edu