van den Hout Multi-State Survival Models for Interval-Censored Data

Erscheinungsjahr 2016
ISBN: 978-1-315-35673-0
Verlag: Taylor & Francis
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 256 Seiten

Reihe: Chapman & Hall/CRC Monographs on Statistics and Applied Probability

Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book is a three-state process for dementia and survival in the older population. This process is described by an illness-death model with a dementia-free state, a dementia state, and a dead state. Statistical modelling of a multi-state process can investigate potential associations between the risk of moving to the next state and variables such as age, gender, or education. A model can also be used to predict the multi-state process.

The methods are for longitudinal data subject to interval censoring. Depending on the definition of a state, it is possible that the time of the transition into a state is not observed exactly. However, when longitudinal data are available the transition time may be known to lie in the time interval defined by two successive observations. Such an interval-censored observation scheme can be taken into account in the statistical inference.
Multi-state modelling is an elegant combination of statistical inference and the theory of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide range of applications.

Zielgruppe

Researchers and graduate students in statistics, biostatistics, demography, social science, and epidemiology.

Autoren/Hrsg.

van den Hout, Ardo

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

Preface
IntroductionMulti-state survival modelsBasic conceptsExamplesOverview of methods and literatureData used in this book
Modelling Survival DataFeatures of survival data and basic terminologyHazard, density and survivor functionParametric distributions for time to event dataRegression models for the hazardPiecewise-constant hazardMaximum likelihood estimationExample: survival in the CAV study
Progressive Three-State Survival ModelFeatures of multi-state data and basic terminologyParametric modelsRegression models for the hazardsPiecewise-constant hazardsMaximum likelihood estimationA simulation studyExample
General Multi-State Survival ModelDiscrete-time Markov processContinuous-time Markov processesHazard regression models for transition intensitiesPiecewise-constant hazardsMaximum likelihood estimationScoring algorithmModel comparisonExampleModel validationExample
Frailty ModelsMixed-effects models and frailty termsParametric frailty distributionsMarginal likelihood estimationMonte-Carlo Expectation-Maximisation algorithmExample: frailty in ELSANon-parametric frailty distributionExample: frailty in ELSA (continued)
Bayesian Inference for Multi-State Survival ModelsIntroductionGibbs samplerDeviance Information Criterion (DIC)Example: frailty in ELSA (continued)Inference using the BUGS software
Redifual State-Specific Life ExpectancyIntroductionDefinitions and data considerationsComputation: integrationExample: a three-state survival processComputation: micro-simulationExample: life expectancies in CFAS
Further TopicsDiscrete-time models for continuous-time processesUsing cross-sectional dataMissing state dataModelling the first observed stateMisclassification of statesSmoothing splines and scoringSemi-Markov models
Matrix P(t) When Matrix Q is ConstantTwo-state modelsThree-state modelsModels with more than three states
Scoring for the Progressive Three-State Model
Some Code for the R and BUGS SoftwareGeneral-purpose optimiserCode for Chapter 2Code for Chapter 3Code for Chapter 4Code for numerical integrationCode for Chapter 6
Bibliography
Index

Über Autor(innen)

Ardo van den Hout