Elizabeth Eisenhauer

Overview

Elizabeth Eisenhauer, PhD, is a Senior Statistical Associate for Statistics and Data Science with 10 years of experience in causal inference, including experiments and quasi-experiments such as interrupted time series and regression discontinuity, and survey sampling and weighting. She integrates quantitative and qualitative perspectives to connect statistical rigor with real-world evaluation practice, applying statistical methods to help answer questions in public health, education, and ecology contexts. Eisenhauer has worked to advance collaboration between statisticians and evaluators by organizing international panels and contributing an article to Amstat News on the topic.

As a part-time instructor at Penn State University, Eisenhauer designs and teaches courses in artificial intelligence (AI), machine learning (ML), survey statistics, and introductory statistics at the undergraduate and graduate levels. She is the 2026 vice chair of the American Statistical Association’s (ASA) Committee on Career Development and a 2026 ASA StatsForward fellow.

In earlier work as a statistical consultant with Penn State University, Eisenhauer developed and vetted statistical models for researchers across disciplines. Her research included advanced parametric and nonparametric models, sampling designs in Bayesian and frequentist inference frameworks, and survey instrument development to assess students’ attitudes.

Education

• PhD, Statistics, Pennsylvania State University
• BA, Mathematics (with a Statistics specialization), The College of New Jersey