Joshua Warren, PhD

• Brian Leaderer
• Daniel Weinberger
• Hongyu Zhao
• Michelle L. Bell
• Nicole Deziel
• Ted Cohen
• Yusuf Ransome

Algorithms; Eye Diseases; Disorders of Environmental Origin; Pregnancy Complications; Probability; Statistics as Topic; Stochastic Processes; Virus Diseases; Statistical Distributions; Biostatistics

Cancer; Environmental Health; Epidemiology Methods; GIS/Disease Mapping; Global Health; Health Policy; Infectious Diseases; Maternal & Child Health; Modeling; Reproduction; Bayesian Statistics; Pollution; COVID-19

• Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure.Warren J, Fuentes M, Herring A, Langlois P. Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure. Biometrics 2012, 68: 1157-67 PubMed ID: 22568640, PMCID: PMC3422613, DOI: 10.1111/j.1541-0420.2012.01774.x.
• Bayesian Spatial-temporal Model for Cardiac Congenital Anomalies and Ambient Air Pollution Risk Assessment.Warren J, Fuentes M, Herring A, Langlois P. Bayesian Spatial-temporal Model for Cardiac Congenital Anomalies and Ambient Air Pollution Risk Assessment. Environmetrics 2012, 23: 673-684 PubMed ID: 23482298, PMCID: PMC3589577, DOI: 10.1002/env.2174.
• Bayesian Spatial Design of Optimal Deep Tubewell Locations in Matlab, Bangladesh.Warren JL, Perez-Heydrich C, Yunus M. Bayesian Spatial Design of Optimal Deep Tubewell Locations in Matlab, Bangladesh. Environmetrics 2013, 24: 377-386 PubMed ID: 24839393, PMCID: PMC4018770, DOI: 10.1002/env.2218.
• Assessment of critical exposure and outcome windows in time-to-event analysis with application to air pollution and preterm birth study.Chang HH, Warren JL, Darrow LA, Reich BJ, Waller LA. Assessment of critical exposure and outcome windows in time-to-event analysis with application to air pollution and preterm birth study. Biostatistics (Oxford, England) 2015, 16: 509-21 PubMed ID: 25572998, PMCID: PMC5963471, DOI: 10.1093/biostatistics/kxu060.
• A Statistical Model to Analyze Clinician Expert Consensus on Glaucoma Progression using Spatially Correlated Visual Field Data.Warren JL, Mwanza JC, Tanna AP, Budenz DL. A Statistical Model to Analyze Clinician Expert Consensus on Glaucoma Progression using Spatially Correlated Visual Field Data. Translational Vision Science & Technology 2016, 5: 14 PubMed ID: 27622079, PMCID: PMC5017314, DOI: 10.1167/tvst.5.4.14.
• Spatially Modelling the Association Between Access to Recreational Facilities and Exercise: The 'Multi-Ethnic Study of Atherosclerosis'.Berchuck SI, Warren JL, Herring AH, Evenson KR, Moore KA, Ranchod YK, Diez-Roux AV. Spatially Modelling the Association Between Access to Recreational Facilities and Exercise: The 'Multi-Ethnic Study of Atherosclerosis'. Journal Of The Royal Statistical Society. Series A, (Statistics In Society) 2016, 179: 293-310 PubMed ID: 26877598, PMCID: PMC4751045, DOI: 10.1111/rssa.12119.
• Bayesian multinomial probit modeling of daily windows of susceptibility for maternal PM2.5 exposure and congenital heart defects.Warren JL, Stingone JA, Herring AH, Luben TJ, Fuentes M, Aylsworth AS, Langlois PH, Botto LD, Correa A, Olshan AF. Bayesian multinomial probit modeling of daily windows of susceptibility for maternal PM2.5 exposure and congenital heart defects. Statistics In Medicine 2016, 35: 2786-801 PubMed ID: 26853919, PMCID: PMC4899303, DOI: 10.1002/sim.6891.
• A Dirichlet process mixture model for clustering longitudinal gene expression data.Sun J, Herazo-Maya JD, Kaminski N, Zhao H, Warren JL. A Dirichlet process mixture model for clustering longitudinal gene expression data. Statistics In Medicine 2017, 36: 3495-3506 PubMed ID: 28620908, PMCID: PMC5583037, DOI: 10.1002/sim.7374.
• A Bayesian semiparametric factor analysis model for subtype identification.Sun J, Warren JL, Zhao H. A Bayesian semiparametric factor analysis model for subtype identification. Statistical Applications In Genetics And Molecular Biology 2017, 16: 145-158 PubMed ID: 28343169, PMCID: PMC5545128, DOI: 10.1515/sagmb-2016-0051.
• Spatial Variability in the Persistence of Pneumococcal Conjugate Vaccine-targeted Pneumococcal Serotypes Among Adults.Warren JL, Pingali SC, Weinberger DM. Spatial Variability in the Persistence of Pneumococcal Conjugate Vaccine-targeted Pneumococcal Serotypes Among Adults. Epidemiology (Cambridge, Mass.) 2017, 28: 119-126 PubMed ID: 27541841, PMCID: PMC5131859, DOI: 10.1097/EDE.0000000000000551.
• Investigating the Impact of Maternal Residential Mobility on Identifying Critical Windows of Susceptibility to Ambient Air Pollution During Pregnancy.Warren JL, Son JY, Pereira G, Leaderer BP, Bell ML. Investigating the Impact of Maternal Residential Mobility on Identifying Critical Windows of Susceptibility to Ambient Air Pollution During Pregnancy. American Journal Of Epidemiology 2018, 187: 992-1000 PubMed ID: 29053768, PMCID: PMC5928458, DOI: 10.1093/aje/kwx335.
• Spatial Modeling to Identify Sociodemographic Predictors of Hydraulic Fracturing Wastewater Injection Wells in Ohio Census Block Groups.Silva GS, Warren JL, Deziel NC. Spatial Modeling to Identify Sociodemographic Predictors of Hydraulic Fracturing Wastewater Injection Wells in Ohio Census Block Groups. Environmental Health Perspectives 2018, 126: 067008 PubMed ID: 29957590, PMCID: PMC6084846, DOI: 10.1289/EHP2663.
• Factors associated with supermarket and convenience store closure: a discrete time spatial survival modelling approach.Warren JL, Gordon-Larsen P. Factors associated with supermarket and convenience store closure: a discrete time spatial survival modelling approach. Journal Of The Royal Statistical Society. Series A, (Statistics In Society) 2018, 181: 783-802 PubMed ID: 29887675, PMCID: PMC5990034, DOI: 10.1111/rssa.12330.
• Investigating spillover of multidrug-resistant tuberculosis from a prison: a spatial and molecular epidemiological analysis.Warren JL, Grandjean L, Moore DAJ, Lithgow A, Coronel J, Sheen P, Zelner JL, Andrews JR, Cohen T. Investigating spillover of multidrug-resistant tuberculosis from a prison: a spatial and molecular epidemiological analysis. BMC Medicine 2018, 16: 122 PubMed ID: 30071850, PMCID: PMC6091024, DOI: 10.1186/s12916-018-1111-x.
• A spatially varying change points model for monitoring glaucoma progression using visual field data.Berchuck SI, Mwanza JC, Warren JL. A spatially varying change points model for monitoring glaucoma progression using visual field data. Spatial Statistics 2019, 30: 1-26 PubMed ID: 30931247, PMCID: PMC6438211, DOI: 10.1016/j.spasta.2019.02.001.
• Critical window variable selection: estimating the impact of air pollution on very preterm birth.Warren JL, Kong W, Luben TJ, Chang HH. Critical window variable selection: estimating the impact of air pollution on very preterm birth. Biostatistics (Oxford, England) 2020, 21: 790-806 PubMed ID: 30958877, PMCID: PMC7422642, DOI: 10.1093/biostatistics/kxz006.
• Diagnosing Glaucoma Progression with Visual Field Data Using a Spatiotemporal Boundary Detection Method.Berchuck SI, Mwanza JC, Warren JL. Diagnosing Glaucoma Progression with Visual Field Data Using a Spatiotemporal Boundary Detection Method. Journal Of The American Statistical Association 2019, 114: 1063-1074 PubMed ID: 31662589, PMCID: PMC6818507, DOI: 10.1080/01621459.2018.1537911.
• A spatially varying distributed lag model with application to an air pollution and term low birth weight study.Warren JL, Luben TJ, Chang HH. A spatially varying distributed lag model with application to an air pollution and term low birth weight study. Journal Of The Royal Statistical Society. Series C, Applied Statistics 2020, 69: 681-696 PubMed ID: 32595237, PMCID: PMC7319179, DOI: 10.1111/rssc.12407.
• Multivariate spatiotemporal modeling of drug- and alcohol-poisoning deaths in New York City, 2009-2014.Ransome Y, Subramanian SV, Duncan DT, Vlahov D, Warren J. Multivariate spatiotemporal modeling of drug- and alcohol-poisoning deaths in New York City, 2009-2014. Spatial And Spatio-temporal Epidemiology 2020, 32: 100306 PubMed ID: 32007280, DOI: 10.1016/j.sste.2019.100306.