Multiple robustness in factorized likelihood models

Authors:
Open Access
Publisher website
Google Scholar
Abstract
We consider inference under a nonparametric or semiparametric model with likelihood that factorizes as the product of two or more variation-independent factors. We are interested in a finite-dimensional parameter that depends on only one of the likelihood factors and whose estimation requires the auxiliary estimation of one or several nuisance functions. We investigate general structures conducive to the construction of so-called multiply robust estimating functions, whose computation requires postulating several dimension-reducing models but which have mean zero at the true parameter value provided one of these models is correct.
Funding Information
  • National Institutes of Health
  • Universidad de Buenos Aires

This publication has 35 references indexed in Scilit: