This repository contains SAS scripts for analyzing experimental design data, focusing on statistical modeling and analysis of treatment effects. It includes projects that demonstrate the use of generalized linear models and factorial design analysis.
Features
- Implementation of generalized linear models (GLM) to analyze treatment effects.
- Factorial design data simulation and analysis.
- Diagnostic plots and normal probability plots for parameter estimates.
- Generation of PDF reports with SAS ODS for results visualization.
Tech Stack
- SAS (Statistical Analysis System) for data manipulation, statistical modeling, and visualization.
Getting Started
Prerequisites
- SAS software installed and licensed.
Running the Projects
- Clone the repository:
git clone https://github.com/justin-napolitano/experimental_design.git
cd experimental_design
-
Open SAS and load either
FInalProject.sasorMidtermProject.sas. -
Run the scripts to perform the analyses. Output files (PDF reports) will be generated at specified paths in the scripts (adjust paths as needed).
Project Structure
FInalProject.sas: Contains data simulation, GLM modeling, estimation, and diagnostic plots for a repeated measures design.MidtermProject.sas: (Assumed) Similar SAS script for midterm project analysis; details not provided.
Future Work / Roadmap
- Parameterize file paths for output reports to improve portability.
- Add comments and documentation within SAS scripts for clarity.
- Include additional experimental designs and analyses.
- Automate report generation and summarization.
- Incorporate data validation and error handling.
Note: This README is based on available code and inferred project scope.