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Regression analysis in an illness-death model with interval-censored data: A pseudo-value approach.
Sabathé, Camille; Andersen, Per K; Helmer, Catherine; Gerds, Thomas A; Jacqmin-Gadda, Hélène; Joly, Pierre.
Affiliation
  • Sabathé C; INSERM, Bordeaux Population Health Research Center, Univ. Bordeaux, Bordeaux, France.
  • Andersen PK; Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
  • Helmer C; INSERM, Bordeaux Population Health Research Center, Univ. Bordeaux, Bordeaux, France.
  • Gerds TA; Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
  • Jacqmin-Gadda H; INSERM, Bordeaux Population Health Research Center, Univ. Bordeaux, Bordeaux, France.
  • Joly P; INSERM, Bordeaux Population Health Research Center, Univ. Bordeaux, Bordeaux, France.
Stat Methods Med Res ; 29(3): 752-764, 2020 03.
Article in En | MEDLINE | ID: mdl-30991888
Pseudo-values provide a method to perform regression analysis for complex quantities with right-censored data. A further complication, interval-censored data, appears when events such as dementia are studied in an epidemiological cohort. We propose an extension of the pseudo-value approach for interval-censored data based on a semi-parametric estimator computed using penalised likelihood and splines. This estimator takes interval-censoring and competing risks into account in an illness-death model. We apply the pseudo-value approach to three mean value parameters of interest in studies of dementia: the probability of staying alive and non-demented, the restricted mean survival time without dementia and the absolute risk of dementia. Simulation studies are conducted to examine properties of pseudo-values based on this semi-parametric estimator. The method is applied to the French cohort PAQUID, which included more than 3,000 non-demented subjects, followed for dementia for more than 25 years.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Models, Statistical Type of study: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Stat Methods Med Res Year: 2020 Document type: Article Affiliation country: France Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Models, Statistical Type of study: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Stat Methods Med Res Year: 2020 Document type: Article Affiliation country: France Country of publication: United kingdom