2022
Models for Zero-Inflated and Overdispersed Correlated Count Data: An Application to Cigarette Use
Pittman B, Buta E, Garrison K, Gueorguieva R. Models for Zero-Inflated and Overdispersed Correlated Count Data: An Application to Cigarette Use. Nicotine & Tobacco Research 2022, 25: 996-1003. PMID: 36318799, PMCID: PMC10077942, DOI: 10.1093/ntr/ntac253.Peer-Reviewed Original ResearchConceptsCorrelated count dataCount outcomesCount dataSubject-specific interpretationZero-InflatedIncorrect statistical inferenceStatistical inferenceCorrelated countsPoisson distributionOverdispersionModel assumptionsPoisson modelRandom effectsHurdle Poisson modelProper modelNegative binomial modelBinomial modelSuch dataAppropriate modelBest fitLarge varianceTobacco researchSuch outcomesModel fitTraining app
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