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BOOK SUMMARY :

Modeling discrete time to event data provides an excellent overview of a field that is underrepresented in the literature at what it aims to do striking a balance between theory and practice this book does a great job its readers will understand not only what to do but also how to do itdiscrete time event history analysis lectures fiona steele and elizabeth washbrook centre for multilevel modelling university of bristol 16 17 july 2013gerhard tutz and matthias schmid 2016 modeling discrete time to event data springer series in statistics doi 101007978 3 319 28158 2 further references gerhard tutz 2012 regression for categorical data cambridge university press hajime uno and tianxi cai and lu tian and l j wei 2007 evaluating prediction rules formore generally they are used to investigate discrete time to event data in homogeneous populations without taking explanatory variables into account the basic life table estimator and smoothed versions are considered the kaplanmeier estimator for continuous time which is closely related to the life table estimator is briefly sketchedtutz gerhard and schmid matthias 2016 modeling discrete time to event data springer series in statistics springer 247 p this work deals primarily with analysis of survival data when a discrete time scale is used books on this type of data usually draw on a more general continuous data framework and tested and confirmed models for

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