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
2017
Replication of a Modified Factor Structure for the Eating Disorder Examination‐Questionnaire: Extension to Clinical Eating Disorder and Non‐clinical Samples in Portugal
Machado PPP, Grilo CM, Crosby RD. Replication of a Modified Factor Structure for the Eating Disorder Examination‐Questionnaire: Extension to Clinical Eating Disorder and Non‐clinical Samples in Portugal. European Eating Disorders Review 2017, 26: 75-80. PMID: 29152813, DOI: 10.1002/erv.2569.Peer-Reviewed Original ResearchConceptsEating Disorder Examination QuestionnaireTreatment-seeking sampleNon-clinical sampleConfirmatory factor analysis findingsDisorder Examination QuestionnaireOriginal scale structureConfirmatory factor analysisFactor analysis findingsExamination QuestionnairePsychometric investigationClinical samplesBrief versionPortuguese sampleDisorder groupFactor structureObese sampleDisorder diagnosisFactor analysisFactor loadingsReliable findingsFemale studentsPoor fitFindingsBest fitAnalysis findings
2014
Combining Epidemiologic and Biostatistical Tools to Enhance Variable Selection in HIV Cohort Analyses
Rentsch C, Bebu I, Guest JL, Rimland D, Agan BK, Marconi V. Combining Epidemiologic and Biostatistical Tools to Enhance Variable Selection in HIV Cohort Analyses. PLOS ONE 2014, 9: e87352. PMID: 24489902, PMCID: PMC3906149, DOI: 10.1371/journal.pone.0087352.Peer-Reviewed Original ResearchConceptsVariable selectionVariable selection approachSignificance testsParsimonious modelInformation theoryBayesian argumentInformation criterionPosterior probabilityBiostatistical proceduresAveraging modelBiostatistical toolsThird methodSelection procedureBest fitSelection approachModelSurvival modelsDifferent methodsTheoryApproachStepwise selection procedureRegression modelsProbabilityStatistical PackageMultivariate regression model
2011
Biomedical Model Fitting and Error Analysis
Costa KD, Kleinstein SH, Hershberg U. Biomedical Model Fitting and Error Analysis. Science Signaling 2011, 4: tr9. PMID: 21954296, PMCID: PMC3272496, DOI: 10.1126/scisignal.2001983.Peer-Reviewed Original ResearchConceptsMathematical modelAppropriate mathematical modelModel parametersError analysisFit parameter valuesLinearization schemeNonlinear modelGoodness of fitNonlinear dataModel fittingBest fitParameter valuesInverse modelingComputational methodsParticular applicationSuch constantsExperimental dataFittingBiomedical systemsProblemFitModelParametersConstantsSeries of measurements
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
1997
Measuring facets of Worry: A Lisrel analysis of the Worry Domains Questionnaire
Joormann J, Stöber J. Measuring facets of Worry: A Lisrel analysis of the Worry Domains Questionnaire. Personality And Individual Differences 1997, 23: 827-837. DOI: 10.1016/s0191-8869(97)00075-5.Peer-Reviewed Original ResearchWorry Domains QuestionnaireDomains QuestionnaireFive-factor modelConfirmatory factor analysisDifferent factor structuresItem-based modelsStable factor loadingsLISREL analysisCluster analytical procedureFactor structureWorry domainsFactor analysisFuture researchSecond sampleNonpathological worryOverall fitFactor loadingsBest fitWorryParticipantsFirst sampleQuestionnaireFitDistinct domainsItems
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