Direct modeling of regression effects for transition probabilities in the progressive illness-death model.
Stat Med
; 36(12): 1964-1976, 2017 05 30.
Article
en En
| MEDLINE
| ID: mdl-28238225
ABSTRACT
In this work, we present direct regression analysis for the transition probabilities in the possibly non-Markov progressive illness-death model. The method is based on binomial regression, where the response is the indicator of the occupancy for the given state along time. Randomly weighted score equations that are able to remove the bias due to censoring are introduced. By solving these equations, one can estimate the possibly time-varying regression coefficients, which have an immediate interpretation as covariate effects on the transition probabilities. The performance of the proposed estimator is investigated through simulations. We apply the method to data from the Registry of Systematic Lupus Erythematosus RELESSER, a multicenter registry created by the Spanish Society of Rheumatology. Specifically, we investigate the effect of age at Lupus diagnosis, sex, and ethnicity on the probability of damage and death along time. Copyright © 2017 John Wiley & Sons, Ltd.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Análisis de Regresión
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Mortalidad
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Modelos Estadísticos
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Progresión de la Enfermedad
Tipo de estudio:
Diagnostic_studies
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Etiology_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Stat Med
Año:
2017
Tipo del documento:
Article
País de afiliación:
Francia