The Statistical Analysis Of Multivariate Failure Time Data: A Marginal Modeling Approach

241 Pages·2019·9.733 MB·English

by  Ross L. Prentice, Shanshan Zhao

The Statistical Analysis of
Multivariate Failure Time
Data
A Marginal Modeling Approach
MONOGRAPHS ON STATISTICS AND APPLIED PROBABILITY
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The Statistical Analysis of
Multivariate Failure Time
Data
A Marginal Modeling Approach
Ross L. Prentice
Shanshan Zhao
CRC Press
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Contents
Preface xi
1 IntroductionandCharacterizationofMultivariateFailureTimeDis-
tributions 1
1.1 FailureTimeDataandDistributions 1
1.2 BivariateFailureTimeDataandDistributions 4
1.3 BivariateFailureTimeRegressionModeling 8
1.4 HigherDimensionalFailureTimeDataandDistributions 9
1.5 MultivariateResponseData:ModelingandAnalysis 11
1.6 RecurrentEventCharacterizationandModeling 12
1.7 SomeApplicationSettings 13
1.7.1 Aplasticanemiaclinicaltrial 13
1.7.2 Australiantwindata 14
1.7.3 Women’sHealthInitiativehormonetherapytrial 15
1.7.4 Bladdertumorrecurrencedata 17
1.7.5 Women’sHealthInitiativedietarymodificationtrial 19
2 UnivariateFailureTimeDataAnalysisMethods 25
2.1 Overview 25
2.2 NonparametricSurvivorFunctionEstimation 25
2.3 HazardRatioRegressionEstimationUsingtheCoxModel 28
2.4 CoxModelPropertiesandGeneralizations 31
2.5 CensoredDataRankTests 32
2.6 CohortSamplingandDependentCensoring 33
2.7 AplasticAnemiaClinicalTrialApplication 35
2.8 WHIPostmenopausalHormoneTherapyApplication 36
2.9 AsymptoticDistributionTheory 40
2.10 AdditionalUnivariateFailureTimeModelsandMethods 44
2.11 ACox-LogisticModelforContinuous,DiscreteorMixedFailure
TimeData 45
3 NonparametricEstimationoftheBivariateSurvivorFunction 51
3.1 Introduction 51
3.2 Plug-InNonparametricEstimatorsofF 52
3.2.1 TheVolterraestimator 52
3.2.2 TheDabrowskaandPrentice–Caiestimators 55
vii
viii
3.2.3 Simulationevaluation 57
3.2.4 Asymptoticdistributionalresults 59
3.3 MaximumLikelihoodandEstimatingEquationApproaches 60
3.4 NonparametricAssessmentofDependency 62
3.4.1 Crossratioandconcordancefunctionestimators 62
3.4.2 Australiantwinstudyillustration 63
3.4.3 Simulationevaluation 65
3.5 AdditionalEstimatorsandEstimationPerspectives 65
3.5.1 Additionalbivariatesurvivorfunctionestimators 65
3.5.2 Estimationperspectives 67
4 RegressionAnalysisofBivariateFailureTimeData 71
4.1 Introduction 71
4.2 IndependentCensoringandLikelihood-BasedInference 72
4.3 CopulaModelsandEstimationMethods 74
4.3.1 Formulation 74
4.3.2 Likelihood-basedestimation 75
4.3.3 Unbiasedestimatingequations 76
4.4 FrailtyModelsandEstimationMethods 78
4.5 AustralianTwinStudyIllustration 79
4.6 RegressiononSingleandDualOutcomeHazardRates 79
4.6.1 Semiparametricregressionmodelpossibilities 79
4.6.2 Cox models for marginal single and dual outcome hazard
rates 80
4.6.3 Dependencymeasuresgivencovariates 82
4.6.4 Asymptoticdistributiontheory 82
4.6.5 Simulationevaluationofmarginalhazardrateestimators 85
4.7 BreastCancerFollowedbyDeathintheWHILow-FatDietInter-
ventionTrial 89
4.8 CountingProcessIntensityModeling 91
4.9 MarginalHazardRateRegressioninContext 92
4.9.1 Likelihoodmaximizationandempiricalplug-inestimators 92
4.9.2 Independentcensoringanddeathoutcomes 92
4.9.3 Marginalhazardratesforcompetingriskdata 93
4.10 Summary 94
5 TrivariateFailureTimeDataModelingandAnalysis 99
5.1 Introduction 99
5.2 NonparametricEstimationoftheTrivariateSurvivorFunction 100
5.2.1 Dabrowska-typeestimatordevelopment 100
5.2.2 Volterraestimator 104
5.2.3 Trivariatedependencyassessment 105
5.2.4 Simulationevaluationandcomparison 106
5.3 TrivariateRegressionAnalysisviaCopulas 109
ix
5.4 RegressiononMarginalSingle,DoubleandTripleFailureHazard
Rates 110
5.5 SimulationEvaluationofHazardRatioEstimators 113
5.6 PostmenopausalHormoneTherapyinRelationtoCVDandMortal-
ity 115
6 HigherDimensionalFailureTimeDataModelingandEstimation 119
6.1 Introduction 119
6.2 NonparametricEstimationofthem-DimensionalSurvivorFunction 120
6.2.1 Dabrowska-typeestimatordevelopment 120
6.2.2 Volterranonparametricsurvivorfunctionestimator 123
6.2.3 Multivariatedependencyassessment 124
6.3 RegressionAnalysisonMarginalSingleFailureHazardRates 125
6.4 RegressiononMarginalHazardRatesandDependencies 129
6.4.1 Likelihoodspecification 129
6.4.2 Estimationusingcopulamodels 130
6.5 MarginalSingleandDoubleFailureHazardRateModeling 133
6.6 CountingProcessIntensityModelingandEstimation 136
6.7 Women’sHealthInitiativeHormoneTherapyIllustration 137
6.8 MoreonEstimatingEquationsandLikelihood 140
7 RecurrentEventDataAnalysisMethods 143
7.1 Introduction 143
7.2 IntensityProcessModelingonaSingleFailureTimeAxis 144
7.2.1 Countingprocessintensitymodelingandestimation 144
7.2.2 Bladdertumorrecurrenceillustration 146
7.2.3 Intensitymodelingwithmultiplefailuretypes 148
7.3 MarginalFailureRateEstimationwithRecurrentEvents 149
7.4 SingleandDoubleFailureRateModelsforRecurrentEvents 151
7.5 WHIDietaryModificationTrialIllustration 151
7.6 AbsoluteFailureRatesandMeanModelsforRecurrentEvents 152
7.7 Perspective on Regression Modeling via Intensities and Marginal
Models 153
8 AdditionalImportantMultivariateFailureTimeTopics 157
8.1 Introduction 157
8.2 DependentCensorship,ConfoundingandMediation 158
8.2.1 Dependentcensorship 158
8.2.2 Confoundingcontrolandmediationanalysis 164
8.3 CohortSamplingandMissingCovariates 166
8.3.1 Introduction 166
8.3.2 Case-cohortandtwo-phasesampling 166
8.3.3 Nestedcase–controlsampling 169
8.3.4 Missingcovariatedatamethods 170
8.4 MismeasuredCovariateData 171