Dr. Hogan conducts research on statistical methods for missing data, causal inference, and sensitivity analysis, with emphasis on applications in HIV/AIDS and behavioral sciences. In the last 2-3 years, the primary emphasis of his research and training efforts is on HIV in sub-Saharan Africa. Current projects concern development of methods for analysis of large-scale observational data, optimizing use of limited resources for clinical monitoring, and analysis of viral sequence data.

Biography

Dr Hogan is a faculty member in the Department of Biostatistics. He is a core faculty member in the Center for Statistical Sciences and serves as Co-Director of the Outcomes and Biostatistics Core for the Center for AIDS Research.

His research concerns the development of statistical methods for missing data, causal inference, and sensitivity analysis, with focus on applications in HIV and behavioral sciences.

Dr Hogan receives funding for his methods research from the NIH, and is an active collaborator on a number of other funded projects.

Institutions

Bu

Research Description

Dr. Hogan's research concerns development of models and methods for analysis of longitudinal data, incomplete data, and observational studies.

Current projects include:

- Statistical methods for observational event history data. Here we are developing methods for sampling and then analyzing data from an electronic medical record system in order to determine the optimal timing of initiation of antiviral therapy for those who are coinfected with HIV and TB.

- Optimal use of limited resources for clinical monitoring. Monitoring individuals on first-line HIV therapy requires use of viral load testing; however, this is a limited resource in much of sub-Saharan Africa. We are developing methods to combine low-cost clinical markers with limited use of more expensive viral load testing to maximize diagnostic accuracy subject to cost constraints.

- Statistical methods for sensitivity analysis with missing data.
(a) formulation of coherent sensitivity analyses for understanding the effects of missing data assumptions on statistical inferences, (b) use of informative prior distributions to characterize assumptions about missing data mechanisms, and (c) use of flexible models such as regression splines for analyzing incomplete longitudinal data.

Awards

Manning Assistant Professor, Brown University (2000-2003)
Fellow of the American Statistical Association (Elected 2008)

Affiliations

Editorial board
Biostatistics

International Consortium
AMPATH Partnership
(Kenya, US, Canada)

Professional Societies
American Statistical Association
International Biometric Society
Institute of Mathematical Statistics
Society of Behavioral Medicine

Funded Research

Current and Recent Grants

Causal Inference Methods for Mediation Analysis
NIH Grant RC1 AA09186
PI: Hogan

Analyzing Complex Longitudinal Data in Behavior Sciences
NIH Grant R01 HL79457
PI: Hogan

Biostatistics Core, Lifespan/Tufts/Brown Center for AIDS Research
NIH Grant P30 AI42853
PI: Charles Carpenter, Miriam Hospital / Brown University


Collaborative Projects

YMCA Exercise Program to Enhance Nicotine Dependence Treatment for Women
NIH Grant R01-DA021729
PI: Bess Marcus

Neuromarkers of Age-Related Cognitive Decline
NIH Grant R01 NS052470
PI: Robert Paul, University of Missouri at St. Louis

Teaching Experience

I teach both introductory and advanced courses in biostatistics.

This fall I am teaching
Principles of Biostatistics (PHP 2510), an introductory course for graduate students in the sciences.

Other courses include Missing Data & Causal Inference (PHP 2610) and Longitudinal Data Analysis (PHP 2603), typically offered in Spring semester.

Selected Publications

• Su L, Hogan JW (2010). HIV dynamics and natural history studies: Joint modeling with interval-­‐censored event times and infrequent longitudinal data. Annals of Applied Statistics, in press.(2010)
• Su L, Hogan JW (2010). Mixtures of varying coefficient models for longitudinal processes with continuous-­‐time informative dropout. Biostatistics 11, 93-­‐110. PMID 19837655. PMCID 2800163(2010)
• Panel on Handling Missing Data in Clinical Trials (2010). The Prevention and Treatment of Missing Data in Clinical Trials (in press). National Academies Press, Washington(2010)
• Kantor R, DeLong A, Kamle L, Muyonga S, Mambo F, Emonyi W, Chan P, Carter EJ, Hogan JW, Buziba N (2009). Misclassification of first line antiretroviral treatment failure based on immunological monitoring of HIV infection in resource-­‐limited settings. Clinical Infectious Diseases 49, 454-­‐462. PMID 19569972(2009)
• Hogan JW (2009). Considerations for sensitivity analysis with likelihood-­‐based models (invited discussion of 'Missing data methods in longitudinal studies: a review' by JG Ibrahim and G Molenberghs). TEST 18, 59-­‐64. Corrections 18, 607.(2009)
• Hogan JW (2009). Bringing causal inference into the mainstream (invited commentary). Epidemiology 20, 431-­‐432. C/R 20, 931-­‐932. PMID 19363354(2009)
• Roy J, Hogan JW, Marcus BH (2008). Principal stratification with predictors of compliance for randomized trials with two active treatments. Biostatistics 9, 277-­‐289. PMID 17681993.(2008)
• Kwara A, DeLong A, Rezk N, Hogan JW, Burtwell H, Chapman S, Moreira CC, Kurpewski J, Ingersoll J, Caliendo AM, Kashuba A, Cu-­‐Uvin S (2008). Antiviral drug concentrations and HIV-­‐1 RNA in the genital tract of HIV-­‐infected women receiving long-­‐term highly active antiretroviral therapy. Clinical Infectious Diseases 46, 719-­‐725. PMID 18220480.(2008)
• Su L, Hogan JW (2008). Bayesian semiparametric regression for longitudinal binary processes with missing data. Statistics in Medicine 27, 3247-­‐3268. PMID 18351709(2008)
• Hogan JW, Liu T (2008). Mediation analysis for intervention trials: objectives, models and inference (invited editorial). Health Services Outcomes Research Methodology 8, 77-­‐79(2008)
• Daniels MJ, Hogan JW (2008). Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis. Chapman & Hall.(2008)
• Hogan JW (2007). Discussion of 'Analysis of longitudinal data with drop-out: Objectives, assumptions and a proposal' by Diggle, Farewell and Henderson. Applied Statistics 56, 530-531.(2007)
• Rich JD, Hogan JW, DeLong AK, Mehrotra M, Reinert SE, Wolf F (2007). Low risk syringe sharing and re-use after syringe legalization in Rhode Island. Drug and Alcohol Dependence 89, 292-297.(2007)
• Committee on Asbestos: Selected Health Effects (2006). Asbestos: Selected Cancers. National Academies Press, Washington.(2006)
• Roy J, Alderson D, Hogan JW, Tashima KT (2006). Conditional inference methods for incomplete Poisson data with endogenous time-varying covariates: Emergency department use among HIV-infected women. Journal of the American Statistical Association 101, 424-434.(2006)
• Hogan JW, Scharfstein DO (2006). Estimating causal effects from multiple cycle data in studies of in vitro fertilization (IVF). Statistical Methods in Medical Research 15, 195-209.(2006)
• Hogan JW, Lin X, Herman B (2004). Mixtures of varying coefficient models for longitudinal data with discrete or continuous non-ignorable dropout. Biometrics 60, 854-864.(2004)
• Hogan JW, Lee JY (2004). Marginal structural quantile models for longitudinal observational studies with time-varying treatment. Statistica Sinica 14, 927-944.(2004)
• Hogan JW, Lancaster T (2004). Instrumental variables and inverse probability weighting for causal inference from longitudinal data. Statistical Methods in Medical Research 13, 17-48.(2004)
• Hogan JW, Roy J, Korkontzelou C (2004). Biostatistics tutorial: Handling dropout in longitudinal data. Statistics in Medicine, 23, 1455-1497.(2004)
• Mahajan A, Hogan JW, Snyder B, Kumarasamy N, Mehta K, Solomon S, Carpenter CCJ, Mayer KH, Flanigan TP (2004). Change in total lymphocyte count as a surrogate for change in CD4 count following initiation of HAART: Implications for monitoring in resource-limited settings. Journal of Acquired Immune Deficiency Syndrome (JAIDS) 36, 567-575.(2004)