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The University of Southampton
CORMSIS Centre for Operational Research, Management Sciences and Information Systems

CORMSIS Seminar - A Simultaneous Equation Approach to Estimating HIV Prevalence with Non-Ignorable Missing Responses Event

14:00 - 15:00
18 May 2017
Room 3041 Building 2, Southampton Business School

For more information regarding this event, please email Dr Yuan Huang at .

Event details

Abstract of the talk: Estimates of HIV prevalence are important for policy in order to establish the health status of a country's population, to evaluate the effectiveness of population-based interventions and campaigns, to identify the most at risk members of the population, and to target those most in need of treatment. However, data in low and middle income countries are often derived from HIV testing conducted as part of household surveys, where participation rates in testing can be low. Low participation rates may be attributed to HIV positive individuals being less likely to participate because they fear disclosure, in which case, estimates obtained using conventional approaches to deal with non-participation, such as imputation-based methods, will be biased. In addition, establishing which population sub-groups are most in need of intervention requires modeling of both spatial dependence and the predictors of HIV status, which is complicated by data censoring due to this non-participation. We develop a Heckman-type selection model framework which accounts for non-ignorable selection, but allows for heterogeneous selection behavior by incorporating a flexible linear predictor structure for modeling dependence structures. The utilization of penalized regression splines and Gaussian Markov random fields allows us to account for non-linear covariate effects and for geographic clustering of HIV. A ridge penalty avoids convergence failures, even when the parameters of the selection (or instrumental) variable are not fully identified. We provide the software for straightforward implementation of this approach, and apply our methodology to estimating national and sub-national HIV prevalence in three sub-Saharan African countries.

Speaker information

Dr Giampiero Marra ,University College London,Giampiero Marra is Associate Professor of Statistics at the Department of Statistical Science, University College London (UCL). After having graduated in Statistics and Economics at the University of Bologna, he was awarded an MSc in Statistics at UCL, and defended his PhD thesis (supervised by Professor Simon N. Wood) at the University of Bath in 2010. He also worked as chief applied econometrician and statistician for two companies (including a consulting firm). He currently teaches and has developed the core module Statistical Models and Data Analysis in the MSc in Statistics and MSc in Computational Statistics and Machine Learning.

Dr Rosalba Radice,University of London,Rosalba Radice is Associate Professor of Statistics at the Department of Economics, Mathematics and Statistics at Birkbeck, University of London. After having graduated in Economics at the University of Bologna, she was awarded an MSc in Statistics at University College London (UCL), and defended her PhD thesis in the field of Phylogenetic Bayesian Networks at the University of Bath in 2010. She also worked at the London School of Hygiene and Tropical Medicine as research fellow. She currently teaches and has been developing various statistical core modules in the MSc in Applied Statistics.

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