2023
ORTH.Ord: An R package for analyzing correlated ordinal outcomes using alternating logistic regressions with orthogonalized residuals
Meng C, Ryan M, Rathouz P, Turner E, Preisser J, Li F. ORTH.Ord: An R package for analyzing correlated ordinal outcomes using alternating logistic regressions with orthogonalized residuals. Computer Methods And Programs In Biomedicine 2023, 237: 107567. PMID: 37207384, DOI: 10.1016/j.cmpb.2023.107567.Peer-Reviewed Original ResearchConceptsOrdinal outcomesSandwich estimatorR packageSimulation studyCorrelated ordinal dataFinite sample biasesNumber of clustersCovariance estimationMarginal modelsEquationsParameter estimatesOrdinal responsesAssociation parametersCluster associationsBias correctionOrdinal dataEstimatorEstimating EquationsNominal levelMarginal meansResidualsEstimationPairwise odds ratiosAssociation modelGEE model
2006
Bayesian modeling for genetic association in case-control studies: accounting for unknown population substructure
Zhang L, Mukherjee B, Ghosh M, Wu R. Bayesian modeling for genetic association in case-control studies: accounting for unknown population substructure. Statistical Modelling 2006, 6: 352-372. DOI: 10.1177/1471082006071841.Peer-Reviewed Original ResearchPopulation substructureCase-control studyGenetic association studiesLog odds ratio parametersOdds ratio parametersAssociation studiesAllele frequenciesGenetic associationParametric Bayesian methodsArgentinean populationBayesian modelCredible intervalsGenetic factorsBayesian methodsStatistical propertiesNumerical integration techniquesPosterior probabilityAssociation modelPopulationAllelesGenesAssociationIntegration techniqueMarkovObesity
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply