Featured Publications
A Bayesian framework for incorporating exposure uncertainty into health analyses with application to air pollution and stillbirth
Comess S, Chang HH, Warren JL. A Bayesian framework for incorporating exposure uncertainty into health analyses with application to air pollution and stillbirth. Biostatistics 2022, 25: 20-39. PMID: 35984351, PMCID: PMC10724312, DOI: 10.1093/biostatistics/kxac034.Peer-Reviewed Original ResearchConceptsFull conditional distributionsEfficient model fittingStatistical modeling approachDensity estimation approachBayesian settingKernel density estimation approachPosterior outputBayesian frameworkConditional distributionModel fittingEstimation approachAccurate inferenceKDE approachModeling approachComparison metricsExposure uncertaintyUncertaintySecond stageApproachFittingInferencePredictionSimulationsModel comparison metricsFirst stage
2016
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: 14-14. PMID: 27622079, PMCID: PMC5017314, DOI: 10.1167/tvst.5.4.14.Peer-Reviewed Original ResearchStatistical modelSpatial probit regression modelsDeviance information criterionModel selection metricsBayesian settingSimulation study resultsModel parametersInformation criterionSpatial modelingCorrelated sensitivityNew methodologySingle frameworkSelection metricsField dataModelProbit regression modelInferenceEstimationVF locationsRegression modelsModelingPredictive abilityNumber of areas