2017
Bayesian Joint Modelling of Longitudinal Data on Abstinence, Frequency and Intensity of Drinking in Alcoholism Trials
Buta E, O’Malley S, Gueorguieva R. Bayesian Joint Modelling of Longitudinal Data on Abstinence, Frequency and Intensity of Drinking in Alcoholism Trials. Journal Of The Royal Statistical Society Series A (Statistics In Society) 2017, 181: 869-888. PMID: 31123390, PMCID: PMC6527419, DOI: 10.1111/rssa.12334.Peer-Reviewed Original ResearchBayesian joint modellingParameter estimate biasStandard frequentist approachRandom effectsLog-normal modelJoint modelFrequentist approachBayesian approachMean squared errorJoint modellingEstimate biasIntensity of drinkingSimulation studyFrequency of drinkingSeparate modellingModellingLongitudinal outcomesClinical trialsSame subjectsSustained abstinenceModelLogistic partAbstinence
2005
Comments about Joint Modeling of Cluster Size and Binary and Continuous Subunit-Specific Outcomes
Gueorguieva RV. Comments about Joint Modeling of Cluster Size and Binary and Continuous Subunit-Specific Outcomes. Biometrics 2005, 61: 862-866. PMID: 16135040, DOI: 10.1111/j.1541-020x.2005.00409_1.x.Peer-Reviewed Original ResearchConceptsCluster sizeJoint modelingContinuous response variablesMaximum likelihood estimatesCluster-level random effectsMaximum likelihood approachData examplesPrior specificationBayesian approachLikelihood estimatesGeneral situationAlternative parameterizationsStandard softwareRandom effectsGeneral modelResponse variablesCluster-level factorsBest fitDunsonExtensive programmingData setsEstimatesModelingModelInference