Inference of a non-parametric covariate-adjusted variable importance measure of a continuous exposureReportar como inadecuado




Inference of a non-parametric covariate-adjusted variable importance measure of a continuous exposure - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1 LAMA - Laboratoire d-Analyse et de Mathématiques Appliquées

Abstract : We consider a setting where a real-valued variable of cause X affects a real-valued variable of effect Y in the presence of a context variable W. The objective is to assess to what extent X, W influences Y while making as few assumptions as possible on the unknown distribution of O = W, X, Y. Based on a user-supplied marginal structural model, our new variable importance measure is non-parametric and context-adjusted. It generalizes the variable importance measure introduced by Chambaz et al. 4. We show how to infer it by targeted minimum loss estimation TMLE, conduct a simulation study and present an illustration of its use.

Keywords : TMLE Inference non-parametric





Autor: Cabral Chanang Tondji -

Fuente: https://hal.archives-ouvertes.fr/



DESCARGAR PDF




Documentos relacionados