PhD, Statistics, Colorado State University
Research interests include: health service research, public health research, diabetes, environmental biostatistics, causal inference, Bayesian inference, regression splines, semi parametric estimation
Honors and service include: Data safety and monitoring board member, Preliminary Investigation of optimaL Oxygen Targets (PILOT) trial; graduate program and staff promotions committees
More information: biostat.app.vumc.org/AmberHackstadt
Dr. Hackstadt's research interests are in the development and application of statistical methods for the exploration and analysis of complex data, which often arise in large public health studies, observational studies and studies utilizing electronic health records. These statistical methods include multiple imputation, semi-parametric regression, causal inference tools, such as propensity scores and principal stratification, and Bayesian modeling. Applications of interest include environmental biostatistics, gestational diabetes, and pharmacoepidemiology, particularly studies related to diabetes.