Statistical Modeling for Biomedical Data Analysis

Comprehensive statistical modeling skill for fitting regression models, survival models, and mixed-effects models to biomedical data. Produces publication-quality statistical summaries with odds ratios, hazard ratios, confidence intervals, and p-values.

Features

✅ Linear Regression - OLS for continuous outcomes with diagnostic tests ✅ Logistic Regression - Binary, ordinal, and multinomial models with odds ratios ✅ Survival Analysis - Cox proportional hazards and Kaplan-Meier curves ✅ Mixed-Effects Models - LMM/GLMM for hierarchical/repeated measures data ✅ ANOVA - One-way/two-way ANOVA, per-feature ANOVA for omics data ✅ Model Diagnostics - Assumption checking, fit statistics, residual analysis ✅ Statistical Tests - t-tests, chi-square, Mann-Whitney, Kruskal-Wallis, etc.

Quick Start

Binary Logistic Regression