2024
Core Concepts in Pharmacoepidemiology: Quantitative Bias Analysis
Brown J, Hunnicutt J, Ali M, Bhaskaran K, Cole A, Langan S, Nitsch D, Rentsch C, Galwey N, Wing K, Douglas I. Core Concepts in Pharmacoepidemiology: Quantitative Bias Analysis. Pharmacoepidemiology And Drug Safety 2024, 33: e70026. PMID: 39375940, DOI: 10.1002/pds.70026.Peer-Reviewed Original ResearchMeSH KeywordsBiasConfounding Factors, EpidemiologicData Interpretation, StatisticalHumansPharmacoepidemiologyResearch DesignSelection BiasConceptsQuantitative bias analysisBias analysisValidity of study findingsPharmacoepidemiological studiesRobustness of studiesEffects of medicationStudy designEffect estimatesResidual biasStudy findingsSelection biasConfoundingEstimated effectsPotential biasPharmacoepidemiologyBiasMedicationCore conceptsStudyMeasurement error
2014
Combining Epidemiologic and Biostatistical Tools to Enhance Variable Selection in HIV Cohort Analyses
Rentsch C, Bebu I, Guest JL, Rimland D, Agan BK, Marconi V. Combining Epidemiologic and Biostatistical Tools to Enhance Variable Selection in HIV Cohort Analyses. PLOS ONE 2014, 9: e87352. PMID: 24489902, PMCID: PMC3906149, DOI: 10.1371/journal.pone.0087352.Peer-Reviewed Original ResearchMeSH KeywordsAntiretroviral Therapy, Highly ActiveBayes TheoremCohort StudiesData Interpretation, StatisticalFemaleHIV InfectionsHumansKaplan-Meier EstimateMaleMultivariate AnalysisProportional Hazards ModelsConceptsVariable selectionVariable selection approachSignificance testsParsimonious modelInformation theoryBayesian argumentInformation criterionPosterior probabilityBiostatistical proceduresAveraging modelBiostatistical toolsThird methodSelection procedureBest fitSelection approachModelSurvival modelsDifferent methodsTheoryApproachStepwise selection procedureRegression modelsProbabilityStatistical PackageMultivariate regression model