projects

PharmaSUG 27

Projects in development for PharmaSUG 2027, focusing on SAS programming, analysis datasets, and statistical inference.

SAS ADaM Core Dataset Skills

Agent skills for developing and checking ADaM datasets in SAS using approved study specifications. The ADSL-first workflow covers ADSL, ADLB, ADVS, ADAE, and ADCM, with derivation traceability, independent QC expectations, and a worked synthetic study example.

View the SAS ADaM Core Dataset Skills repository

Robust Covariate Adjustment under CAR in SAS

A SAS Viya research implementation of continuous-outcome augmented inverse probability weighting (AIPW), joint calibration, CAR variance estimation, and treatment contrasts. The repository includes analysis workflows, documentation, and comparisons against RobinCar 1.2.0.

View the Robust Covariate Adjustment repository

Statistical tools and research software I have developed or contributed to, spanning clinical study design and reproducible inference.

pppower

Power and sample size planning

R tools for planning studies that use prediction-powered inference.

My contribution: Co-developed the R package, with modular functions, CI testing, documentation, and simulation studies of statistical performance.

Tools and methods: R · Monte Carlo simulation · CI/testing

PlanMCI

Study design under budget constraints

ANCOVA-based power and minimum detectable effect calculations for mild cognitive impairment trials.

My contribution: Developed the R package and interactive Shiny app to explore feasible designs and power under study budget constraints.

Tools and methods: R · Shiny · ANCOVA

LLM evaluation

Inference with noisy automated judgments

Statistical debiasing methods for LLM-as-a-judge evaluation.

My contribution: Conducted simulation studies comparing Rogan–Gladen and PPI/PPI++ estimators, assessing bias, interval coverage, and interval width.

Tools and methods: R · Monte Carlo simulation · Prediction-powered inference

GitHub

Explore my public repositories, code, and contributions on GitHub.

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