2020
Interaction analysis under misspecification of main effects: Some common mistakes and simple solutions
Zhang M, Yu Y, Wang S, Salvatore M, Fritsche L, He Z, Mukherjee B. Interaction analysis under misspecification of main effects: Some common mistakes and simple solutions. Statistics In Medicine 2020, 39: 1675-1694. PMID: 32101638, DOI: 10.1002/sim.8505.Peer-Reviewed Original ResearchConceptsType I error rateType I error inflationIndependence assumptionWald and score testsCorrect type I error ratesSandwich variance estimatorSandwich estimatorScore testVariance estimationSimulation studyMisspecificationMichigan Genomics InitiativeStatistical practiceBinary outcomesTested interactionsEmpirical factsFlexible modelData modelTest of interactionBiobank studyInflationAssumptionsContinuous outcomesEpidemiological literatureLinear regression models
2008
Fitting stratified proportional odds models by amalgamating conditional likelihoods
Mukherjee B, Ahn J, Liu I, Rathouz P, Sánchez B. Fitting stratified proportional odds models by amalgamating conditional likelihoods. Statistics In Medicine 2008, 27: 4950-4971. PMID: 18618428, PMCID: PMC3085191, DOI: 10.1002/sim.3325.Peer-Reviewed Original ResearchConceptsNuisance parametersConditional likelihoodProportional odds modelStratum-specific nuisance parametersCumulative logit modelStratum-specific interceptsGeneral regression frameworkMultiple ordered categoriesOdds modelContinuous covariatesSandwich estimatorData examplesBinary exposureRobust sandwich estimatorLikelihood principleProportional oddsStandard softwareRegression frameworkNatural choiceOutcome modelEstimationClassical methodsStratified dataLogistic regression modelsRandom-effects model