Print Email Facebook Twitter Bayesian inference for an illness-death model for stroke with cognition as a latent time-dependent risk factor Title Bayesian inference for an illness-death model for stroke with cognition as a latent time-dependent risk factor Author van den Hout, A. Fox, J.P. Publication year 2015 Abstract Longitudinal data can be used to estimate the transition intensities between healthy and unhealthy states prior to death. An illness-death model for history of stroke is presented, where time-dependent transition intensities are regressed on a latent variable representing cognitive function. The change of this function over time is described by a linear growth model with random effects. Occasion-specific cognitive function is measured by an item response model for longitudinal scores on the Mini-Mental State Examination, a questionnaire used to screen for cognitive impairment. The illness-death model will be used to identify and to explore the relationship between occasion-specific cognitive function and stroke. Combining a multi-state model with the latent growth model defines a joint model which extends current statistical inference regarding disease progression and cognitive function. Markov chain Monte Carlo methods are used for Bayesian inference. Data stem from the Medical Research Council Cognitive Function and Ageing Study in the UK (1991-2005). © SAGE Publications. Subject LifeRAPID - Risk Analysis for Products in DevelopmentELSS - Earth, Life and Social SciencesBiomedical InnovationBiologyHealthy LivingItem-response theoryMarkov chain Monte CarloMulti-state modelRandom effectsAgedAlgorithmBayesian inferenceCause of deathCerebrovascular accidentCognitionCognitive defectHumanLinear systemMajor clinical studyMathematical analysisMathematical modelMental performanceMini Mental State ExaminationMonte Carlo methodPredictionProbabilityRisk factor To reference this document use: http://resolver.tudelft.nl/uuid:1be15fdd-c324-4d14-8641-5af430851800 DOI https://doi.org/10.1177/0962280211426359 TNO identifier 530122 ISSN 0962-2802 Source Statistical Methods in Medical Research, 24 (6), 769-787 Document type article Files To receive the publication files, please send an e-mail request to TNO Library.