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
2018
Models for Analyzing Zero-Inflated and Overdispersed Count Data: An Application to Cigarette and Marijuana Use
Pittman B, Buta E, Krishnan-Sarin S, O’Malley S, Liss T, Gueorguieva R. Models for Analyzing Zero-Inflated and Overdispersed Count Data: An Application to Cigarette and Marijuana Use. Nicotine & Tobacco Research 2018, 22: 1390-1398. PMID: 29912423, PMCID: PMC7364829, DOI: 10.1093/ntr/nty072.Peer-Reviewed Original ResearchZero-inflated negative binomialZero-inflationZero-inflated PoissonNegative binomialAbundance of zerosCount dataIllustrative data exampleCount outcomesHurdle PoissonData examplesZINB modelFit statisticsPoissonLarge positive skewModel fitZerosNB modelBinomialAppropriate modelHurdle modelLarge varianceSpurious resultsModelOverdispersionSuch data