There is a strong push to conduct large-scale randomized controlled study designs in HIV prevention studies. In these randomized controlled studies, the primary research objective is typically to determine the treatment effect based on some biological outcome (e.g. HIV infection). Millions of dollars are spent on these studies and lots of resources are spent towards collecting data on self-reported outcomes, even when such outcomes are of great interest but rarely utilized. The majority of these self-reported outcomes are never utilized in statistical analyses and we question whether the extent they are used justifies the cost, researcher’s and subject’s burden. In this presentation we will touch on some findings from the EXPLORE data, discuss some meta-analysis results on the relationship between self-reported and biological outcomes, and look at the utility of study designs with planned missingness. This is work in progress.
Ofer Harel, Ph.D. is an associate professor in the Department of Statistics and a principal Investigator in the Center for Health, Intervention, and Prevention (CHIP) at the University of Connecticut. Dr. Harel received his doctorate in statistics in 2003 from the Pennsylvania State University. Dr. Harel received his post-doctoral training at the University of Washington, Department of Biostatistics, where he worked for the HSR&D Center of Excellence, VA Puget Sound Healthcare System, and the National Alzheimer’s Coordinating Center (NACC). Dr. Harel has served as a biostatistical consultant nationally and internationally since 1997. Through his collaborative consulting, Dr. Harel has been involved with a variety of research fields including, but not limited to Alzheimer’s, diabetes, nutrition, HIV/AIDS, and alcohol and drug abuse prevention.