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
2001
A multivariate generalized linear mixed model for joint modelling of clustered outcomes in the exponential family
Gueorguieva R. A multivariate generalized linear mixed model for joint modelling of clustered outcomes in the exponential family. Statistical Modelling 2001, 1: 177-193. DOI: 10.1177/1471082x0100100302.Peer-Reviewed Original ResearchExponential familyMonte Carlo EM algorithmJoint multivariate normal distributionGeneralized linear mixed modelMultivariate normal distributionMaximum likelihood estimation approachRandom effectsMultivariate caseData examplesMultivariate generalizationEM algorithmJoint modellingMultiple outcome variablesRestrictive assumptionsEstimation approachMeasures dataNormal distributionLinear mixed modelsMore variablesScore testMixed modelsSingle modelData setsAssumptionQuadrature