2020
Two‐part models for repeatedly measured ordinal data with “don't know” category
Gueorguieva R, Buta E, Morean M, Krishnan‐Sarin S. Two‐part models for repeatedly measured ordinal data with “don't know” category. Statistics In Medicine 2020, 39: 4574-4592. PMID: 32909252, PMCID: PMC8025667, DOI: 10.1002/sim.8739.Peer-Reviewed Original ResearchConceptsAdaptive Gaussian quadratureCorrelated random effectsSAS PROC NLMIXEDOrdinal dataMaximum likelihood estimationTerms of biasStatistical dependenceNominal modelGaussian quadraturePROC NLMIXEDLikelihood estimationPartial orderingEstimation algorithmTwo-part modelModel formulationSimulation studyRandom effectsPredictor effectsSubmodelsOrdinal natureFormulationNLMIXEDQuadratureModelOrdering
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