StatShare Community of Practice

About StatShare

Welcome to the StatShare web page!

StatShare is a community of practice for non-faculty biostatisticians to share knowledge, learn, network, and support one another in solving difficult research problems they encounter in their work.

Dr. Kathleen Wannemuehler and Dr. Bret Hanlon, both Scientists in Biostatististics and Medical Informatics, lead StatShare.

If you have ideas for StatShare meetings, please reach out to Dr. Wannemuehler at or Dr. Hanlon at

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How Does it Work?

When do we meet?

The StatShare community meets on the second Tuesday of the month during the academic year from 10:30-11:30 am.

Who Attends?

Non-faculty biostatisticians who are engaged in biomedical research are welcome to attend.

Get StatShare Updates

Get StatShare Updates

Submit your name, email, and department to request addition to the StatShare google mailing list.

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Upcoming Events

October 10, 2023

Speaker: Colin Longhurst

Title: Pharma Internship (GSK) Experience

Time: 10:30-11:30 am


Abstract: Biomedical Data Sciences PhD student Colin Longhurst will discuss his 2023 summer internship experience with GlaxoSmithKline, a large pharmaceutical company.

November 14, 2023

Speaker: Jacky Kruser

Title: Time-limited Trials to Improve the Care of Mechanically Ventilated Adults

Time: 10:30-11:30 am


December 12, 2023

Speaker: Jake Maronge

Title: A Bayesian Phase II Design with Adaptive Clustering and Matching to Historical Controls

Time: 10:30-11:30 am


2023-24 StatShare Events

2022-23 Statshare Events

December 13, 2022

Speaker: Jen Birstler

Title: R Markdown for ‘old R Sweave dogs’
Abstract: Learn about R Markdown, its interactive features within RStudio, and supporting packages (knitr, kableExtra, plotly) to use for creating reports (pdf, html). With RStudio rebranding into Posit and recently launching Quarto, we’ll discuss its potential impact on the future of R.

November 8, 2022

Speaker: Noah Greifer, Data Science Specialist, Institute for Quantitative Social Science, Harvard University

Title: Computational Tools for Implementing Best Practices in Propensity Score Analysis

Abstract: Propensity score analysis, including matching and weighting, is a popular method to adjust for confounding by measured confounding variables in observational studies. Rather than (or in addition to) including confounding variables in a regression of the outcome on the treatment, propensity score methods involve manipulating the sample to mimic the qualities of a randomized trial. In this talk, I will introduce propensity score analysis and describe a suite of R packages that can be used to implement best practices in their application. These packages include MatchIt, WeightIt, cobalt, and several auxiliary packages for more specialized cases and for implementing emerging methods.

October 11, 2022

Speaker: Hyunseung Kang, Assistant Professor, Department of Statistics, University of Wisconsin-Madison

Title: Optimal Allocation of Water and Sanitation Facilities To Prevent Communicable Diarrheal Diseases in Senegal Under Partial Interference

Abstract: For several decades, Senegal has faced inadequate water, sanitation, and hygiene (WASH) facilities in households, contributing to persistent, high levels of communicable diarrheal diseases. Unfortunately, the ideal WASH policy where every household in Senegal installs WASH facilities is impossible due to logistical and budgetary concerns. This work proposes to estimate an optimal allocation rule of WASH facilities in Senegal by combining recent advances in personalized medicine and partial interference in causal inference. Our allocation rule helps public health officials in Senegal decide what fraction of total households in a region should get WASH facilities based on block-level and household-level characteristics. We characterize the excess risk of the allocation rule and show that our rule outperforms other allocation policies in Senegal.

This is joint work with Chan Park (University of Pennsylvania), Guanhua Chen (UW-Madison), and Menggang Yu (UW-Madison).

2021-22 StatShare Events

Assumption-lean Analysis of Cluster Randomized Trials in Infectious Diseases for Intent-to-Treat Effects and Network Effect

Hyunseung Kang

May 17, 2022

A case study in reproducible report generation: communicating quality metrics to Wisconsin surgical health care providers

Bret Hanlon and Jessica Schumacher

April 12, 2022

Importing Datasets in PostgreSQL and REDCap via ETL

Keith Wanta

March 15, 2022

tidyverse and ggplot2 for old R dogs

Jen Birstler

February 15, 2022

Big Data to Detect and Prevent Clinical Deterioration

Matt Churpek

January 11, 2022