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 ResearchMeSH KeywordsBiasCluster AnalysisComputer SimulationHumansLogistic ModelsLongitudinal StudiesModels, StatisticalConceptsOrdinal 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
2020
Propensity score weighting for covariate adjustment in randomized clinical trials
Zeng S, Li F, Wang R, Li F. Propensity score weighting for covariate adjustment in randomized clinical trials. Statistics In Medicine 2020, 40: 842-858. PMID: 33174296, DOI: 10.1002/sim.8805.Peer-Reviewed Original ResearchMeSH KeywordsComputer SimulationHumansLogistic ModelsPropensity ScoreRandomized Controlled Trials as TopicResearch Design