This project analyzes HIV randomized clinical trial data (2,100+ patients) to study treatment effects on CD4 cell counts over time using R. Linear models were used to evaluate both initial treatment response and prolonged clinical benefit. The analysis examines interaction effects and covariate influences, with statistical inference applied to assess treatment outcomes.
Skills demonstrated:
- Data cleaning and preprocessing (missing value handling, factor handling, filtering)
- Exploratory data analysis (EDA) and visualizations
- Linear modeling with interaction terms and covariates
- Hypothesis testing (t-tests, partial F-tests)
- Model diagnostics including residual and leverage analysis
Files in repository:
hiv_rct_analysis.qmd: Quarto file containing code, visualizations, and documentation of analysis.hiv_report.pdf: Full writeup of analytical findings, following IMRaD structure.