Dr. Goldstick is the Director of Statistics and Methods in the CDC-funded University of Michigan Injury Prevention Center (UMIPC) and a Research Associate Professor of Emergency Medicine and Health Behavior and Health Education at the University of Michigan. Dr. Goldstick is a statistician by training and his past research spans several areas of social epidemiology including infectious disease, childhood problem behaviors, substance use, and violence. He has extensive expertise in statistical analyses, including predictive modeling and the analysis of longitudinal and spatially dependent data, especially as it applies to substance use, injury/violence data, and public health research. He has been the PI of a NIDA grant to study age-dependence in the predictors of substance use and its comorbidities, an NIAAA grant-funded to study predictors of alcohol use transitions and how those transitions coalesce with transitions in other health behaviors, and has received CDC contracts to use administrative claims data to study changes in opioid prescribing and related outcomes following the release of the CDC Guideline for Prescribing Opioids for Chronic Pain. His current and ongoing work focuses on violence and substance use epidemiology, overdose surveillance, and estimating behavioral intervention treatment effects. Specifically, Dr. Goldstick is currently PI of an R01 funded to use machine learning methods to optimally predict future violence involvement, and directs a statewide near real-time surveillance system for opioid overdoses in Michigan called the System for Opioid Overdose Surveillance, and is the lead statistician on over a half dozen current federally funded studies.
Dr. Goldstick's Firearm-Related Work
U-M experts available to discuss prevention, aftermath of school shooting in Texas
School shooting in Uvalde, Texas brings awareness to recent data showing firearms are the leading cause of death for children in the U.S.
U-M Researchers Respond to School Shooting in Ulvade, Texas
Firearms now top cause of death among children, adolescents, U-M analysis shows