Choice between Semi-parametric Estimators of Markov and Non-Markov Multi-state Models from Coarsened Observations
| hal.structure.identifier | Biostatistique | |
| hal.structure.identifier | Epidémiologie, santé publique et développement | |
| dc.contributor.author | COMMENGES, Daniel | |
| hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
| hal.structure.identifier | Quality control and dynamic reliability [CQFD] | |
| dc.contributor.author | GÉGOUT-PETIT, Anne | |
| hal.structure.identifier | Biostatistique | |
| dc.contributor.author | JOLY, Pierre | |
| hal.structure.identifier | Biostatistique | |
| hal.structure.identifier | Institut de Santé Publique, d'Epidémiologie et de Développement [ISPED] | |
| hal.structure.identifier | Laboratoire de Statistiques et Analyse des Données [LABSAD] | |
| hal.structure.identifier | Statistique Appliquée et de Géométrie Aléatoire de Grenoble [SAGAG] | |
| dc.contributor.author | LIQUET, Benoit | |
| dc.date.created | 2006 | |
| dc.date.issued | 2007-03 | |
| dc.identifier.issn | 0303-6898 | |
| dc.description.abstractEn | We consider models based on multivariate counting processes, including multi‐state models. These models are specified semi‐parametrically by a set of functions and real parameters. We consider inference for these models based on coarsened observations, focusing on families of smooth estimators such as produced by penalized likelihood. An important issue is the choice of model structure, for instance, the choice between a Markov and some non‐Markov models. We define in a general context the expected Kullback–Leibler criterion and we show that the likelihood‐based cross-validation (LCV) is a nearly unbiased estimator of it. We give a general form of an approximate of the leave‐one‐out LCV. The approach is studied by simulations, and it is illustrated by estimating a Markov and two semi‐Markov illness–death models with application on dementia using data of a large cohort study. | |
| dc.language.iso | en | |
| dc.publisher | Wiley | |
| dc.subject.en | counting processes | |
| dc.subject.en | cross-validation | |
| dc.subject.en | dementia | |
| dc.subject.en | interval-censoring | |
| dc.subject.en | Kullback–Leibler loss | |
| dc.subject.en | Markov models | |
| dc.subject.en | multi-state models | |
| dc.subject.en | penalized likelihood | |
| dc.subject.en | semi-Markov models | |
| dc.title.en | Choice between Semi-parametric Estimators of Markov and Non-Markov Multi-state Models from Coarsened Observations | |
| dc.type | Article de revue | |
| dc.identifier.doi | 10.1111/j.1467-9469.2006.00536.x | |
| dc.subject.hal | Mathématiques [math]/Statistiques [math.ST] | |
| dc.subject.hal | Statistiques [stat]/Théorie [stat.TH] | |
| bordeaux.journal | Scandinavian Journal of Statistics | |
| bordeaux.page | 33-52 | |
| bordeaux.volume | 34 | |
| bordeaux.issue | 1 | |
| bordeaux.peerReviewed | oui | |
| hal.identifier | hal-00194275 | |
| hal.version | 1 | |
| hal.popular | non | |
| hal.audience | Internationale | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-00194275v1 | |
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