2010
Missing Exposure Data in Stereotype Regression Model: Application to Matched Case–Control Study with Disease Subclassification
Ahn J, Mukherjee B, Gruber S, Sinha S. Missing Exposure Data in Stereotype Regression Model: Application to Matched Case–Control Study with Disease Subclassification. Biometrics 2010, 67: 546-558. PMID: 20560931, PMCID: PMC3119773, DOI: 10.1111/j.1541-0420.2010.01453.x.Peer-Reviewed Original ResearchConceptsStereotype regression modelSubtypes of casesDeletion of observationsExpectation/conditional maximization algorithmBaseline category logit modelEstimation of model parametersMissingness mechanismData mechanismCase-control dataProportional oddsBayesian approachCategorical responsesCase-control studyCase-control study of colorectal cancerMissingnessMaximization algorithmCategorical outcomesMonte CarloModel assumptionsRegression modelsStudy of colorectal cancerModel parametersNonidentifiabilityDisease subclassificationMultinomial logit model
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