2023
The first nicotine product tried is associated with current multiple nicotine product use and nicotine dependence among a nationally representative sample of U.S. youths
Simon P, Buta E, Jackson A, Camenga D, Kong G, Morean M, Bold K, Davis D, Krishnan-Sarin S, Gueorguieva R. The first nicotine product tried is associated with current multiple nicotine product use and nicotine dependence among a nationally representative sample of U.S. youths. Preventive Medicine 2023, 169: 107437. PMID: 36731754, PMCID: PMC10507373, DOI: 10.1016/j.ypmed.2023.107437.Peer-Reviewed Original ResearchConceptsNicotine product useSymptoms of dependenceNicotine dependenceMultiple product useSmokeless tobaccoNicotine productsProduct useSeparate multinomial logistic regression modelsHealth Study Waves 1Wave 1Smokeless tobacco usersHigher nicotine dependence scoresNicotine dependence scoresDemographic factorsLogistic regression modelsMultinomial logistic regression modelsMultivariable modelTobacco usersHigh riskDependence scoresSymptomsGreater likelihoodUse statusWave 4Regression models
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