This tutorial outlines the process of performing and interpreting an ordinal logistic regression analysis using the clm function from the ordinal package in R.

This tutorial demonstrates how to build a prediction model using the XGBoost machine learning classification technique.

This tutorial demonstrates how to use `ggplot2` from the `tidyverse` package to create advanced, highly customizable data visualizations while telling the story of bike thefts in Toronto through data, presented across 5 chapters.

This document demonstrates Target Trial Emulation in R. It covers defining estimands, preparing observational data, handling censoring via IPCW, expanding data into trial sequences, and fitting marginal structural models. Predictions, such as survival probabilities, are generated and visualized to assess treatment effects.

This script creates custom forest plots in R to visualize effect size measures and confidence intervals for multiple groups. It combines structured data, customized aesthetics, and unified plots for clear comparisons and effective presentation.

This website features my professional background, interactive tools, and tutorials related to biostatistics, data science, and health economics. Explore my work to learn how data-driven insights are applied to healthcare research and decision-making.