Using Interviewer Random Effects to Calculate Unbiased HIV Prevalence Estimates in the Presence of Non-Response: A Bayesian Approach • Mark E. McGovern, Harvard University ; David Canning, Harvard University

Respondent-Driven Sampling and Time-Location Sampling: A Comparison of Implementation and Operational Challenges for HIV Behavioral Research • Marissa Hall, University of North Carolina at Chapel Hill ; Clare Barrington, University of North Carolina at Chapel Hill ; Sanny Y. Chen, Centers for Disease Control and Prevention (CDC) ; Nelson Arambu, Universidad del Valle de Guatemala ; Sonia Morales, Universidad del Valle de Guatemala ; William M. Miller, University of North Carolina at Chapel Hill ; Berta Alvarez, Universidad del Valle de Guatemala ; Gabriela Paz-Bailey, Universidad del Valle de Guatemala

Modeling the Impact of Post-Diagnosis Behavior Change on HIV Prevalence in Southern California Men Who Have Sex with Men (MSM) • Aditya Khanna, University of Washington ; Steven M. Goodreau, University of Washington ; Pamina Gorbach, University of California, Los Angeles

Decomposing Gender Inequalities in HIV/AIDS in Kenya, Lesotho and Tanzania • Drissa Sia, McGill University ; Yentéma Onadja, Université de Montréal ; Arijit Nandi, McGill University ; Anne Foro, École Nationale d’adminstration Publique, Montréal ; Timothy Brewer, McGill University