Dr. Andre Waschka

Education

• Ph.D. in Statistics, University of California, Berkeley
• M.A. in Biostatistics, University of California, Berkeley
• B.S. in Applied Mathematics, North Carolina State University
• B.S. in Economics, North Carolina State University

Specialty

Statistics

Professional Interests

Dr. Andre Waschka’s research interests are applied statistics and spans biostatistics, data science, and machine learning. He works on semi-parametric and parametric statistical models that involve high dimensional data and use causal framework and machine learning to estimate targeted parameters and obtain causal inference. Most of his work is motivated by problems from biomedical fields with application to treatment regime protocols and precision medicine. His current projects include:

• Detecting and Mitigating Positivity Violations in Highly Dimensional Complex Longitudinal Studies
• A Semi-Parametric Bootstrap Simulation Method Generating Simulated Datasets from the Original Data
• Causal Effect Models for Realistic Treatment Rules in Complex Longitudinal Settings
• Developing Treatment Rules that Optimize Health Outcomes Using Super Learning and Tree-Regression
• Estimating When to Switch Treatment for Hypotensive ICU Patients Using Longitudinal Targeted Maximum Likelihood Estimation

Recent Publications

• The effects of low dose hydrocortisone and hydrocortisone plus fludrocortisone in adults with septic shock: a protocol for a systematic review and meta-analysis of individual participant data, (D. Annane, R. Pirracchio, L. Billot, A. Waschka et al.) BMJ Open 2020;10:e040931. doi:10.1136/bmjopen-2020-040931.

Contact Dr. Andre Waschka

(478) 301-2814
waschka_ak@mercer.edu
Office: Ware Hall, Room 110A