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Joint Model for Longitudinal and Survival Data

The joint model for longitudinal and time-to-event data, formalised by Tsiatis and Davidian in 2004 and extended comprehensively by Rizopoulos in 2012, simultaneously estimates a mixed-effects model for repeatedly measured biomarkers and a survival model for the time to an event, linking the two processes through shared random effects. It resolves two major problems that simpler approaches cannot handle: informative dropout from longitudinal studies and the endogeneity of time-varying biomarkers used as covariates in a Cox model.

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Joint Model for Longitudinal and Time-to-Event Data

Taksonoomiline meetodikirje · survival / survival

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Same method familyFrailty Modelmachine-suggested · Relational suggestion, not evidence.Same method familyKaplan-Meiermachine-suggested · Relational suggestion, not evidence.Same method familyLandmark Analysismachine-suggested · Relational suggestion, not evidence.See alsoMixed Effects Modelmachine-suggested · Relational suggestion, not evidence.Same method familyTime-Dependent Cox Regressionmachine-suggested · Relational suggestion, not evidence.