Methods Core Seminars

Upcoming seminar


Title:           Optimally Combining Outcomes To Improve Prediction

Presenter:    David Benkeser, PhD

Post-doctoral researcher in the Department of Biostatistics,

UC Berkeley

 Date:             Tuesday, March 7, 2017

Time:              2-4

Location:       AmFAR Conference room MH-3700

550 16th Street (at 4th Street), 3rd Floor

Mission Bay, SF 94158


In many studies, multiple instruments are used to measure different facets of an unmeasured outcome of interest. For example, in studies of childhood development, children are administered tests in several areas and researchers combine these test scores into a univariate measure of neurocognitive development. Researchers are interested in predicting this development score based on household and environment characteristics early in life in order to identify children at high risk for neurocognitive delays. We propose a method for estimating the combined measure that maximizes predictive performance. Our approach allows modern machine learning techniques to be used to predict the combined outcome using potentially high-dimensional covariate information. In spite of the highly adaptive nature of the procedure, we nevertheless obtain valid estimates of the prediction algorithm’s performance for predicting the combined outcome as well as confidence intervals about these estimates. We illustrate the methodology using longitudinal cohort studies of early childhood development.

Bio:   David Benkeser is a post-doctoral researcher in the Department of Biostatistics working with Dr. Mark van der Laan. My research interests revolve around causal inference and machine learning. I am currently working with the Bill and Melinda Gates Foundation’s Healthy Birth, Growth, and Development initiative aimed at identifying children at high risk for developmental deficits in the developing world and developing targeted interventions to help these children. I received my PhD. from the University of Washington Department of Biostatistics where my research focused on methods for evaluating vaccines, particularly for prevention of HIV and malaria. I have also worked extensively in cardiovascular epidemiology and health care economics at end-of-life.

If you are coming from outside Mission Hall, please RSVP to Estie Hudes to be put on the building security list.


Materials from past seminars



  • January 20, 2017 – Carl A. Latkin, PhD: Randomized clinical trials of social network approaches to HIV prevention and care: Lessons learned
  • May 17, 2016 —   John A. Schneider MD, MPH, PhD: Social Network Data Collection Approaches and Strategies for Introductory Analysis and Intervention PlanningVideo
  • May 3, 2016 — Tor Neilands, PhD, Kim Koester, MA & Troy Wood, MA: An Introduction to Survey Scale Development and Cognitive Interviewing
  • April 19-20, 2016 — Blair Johnson, PhD & Tania Huedo-Medina, PhD: Meta-Analysis workshop