2012
Point source modeling of matched case–control data with multiple disease subtypes
Li S, Mukherjee B, Batterman S. Point source modeling of matched case–control data with multiple disease subtypes. Statistics In Medicine 2012, 31: 3617-3637. PMID: 22826092, PMCID: PMC4331356, DOI: 10.1002/sim.5388.Peer-Reviewed Original ResearchConceptsAdjacent-category logit modelMarkov chain Monte Carlo techniquesEvaluate maximum likelihoodExtensive simulation studyProfile likelihoodHierarchical Bayesian approachCase-control dataSimulation studyBayesian approachMonte Carlo techniqueBayesian methodsMaximum likelihoodMultiple disease subtypesCategorical outcomesCovariate adjustmentNonlinear modelEstimation stabilityMedicaid claims dataCase-control designPediatric asthma populationAsthma populationElevated oddsMarkovLogit modelCovariates
2007
Analysis of matched case–control data with multiple ordered disease states: possible choices and comparisons
Mukherjee B, Liu I, Sinha S. Analysis of matched case–control data with multiple ordered disease states: possible choices and comparisons. Statistics In Medicine 2007, 26: 3240-3257. PMID: 17206600, DOI: 10.1002/sim.2790.Peer-Reviewed Original ResearchConceptsConditional logistic regressionStratum-specific nuisance parametersCase-control dataAdjacent-category logit modelCase-control studyOrdered categorical dataConditional-likelihood approachLikelihood-based approachNuisance parametersProportional-odds modelCumulative logitsSimulation studyAnalyse such dataMantel-Haenszel approachCumulative logit modelNatural orderPotential risk factorsStages of cancerReference categoryCategorical dataLogistic regressionOrdinal natureEffect of potential risk factorsLow birthweightRisk factors