Improved double-robust estimation in missing data and causal inference models

Recently proposed double-robust estimators for a population mean from incomplete data and for a finite number of counterfactual means can have much higher efficiency than the usual double-robust estimators under misspecification of the outcome model. In this paper, we derive a new class of double-ro...

Descripción completa

Detalles Bibliográficos
Autor principal: Sued, Mariela
Publicado: 2012
Materias:
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00063444_v99_n2_p439_Rotnitzky
http://hdl.handle.net/20.500.12110/paper_00063444_v99_n2_p439_Rotnitzky
Aporte de:
id paper:paper_00063444_v99_n2_p439_Rotnitzky
record_format dspace
spelling paper:paper_00063444_v99_n2_p439_Rotnitzky2023-06-08T14:31:12Z Improved double-robust estimation in missing data and causal inference models Sued, Mariela Drop-out Marginal structural model Missing at random Recently proposed double-robust estimators for a population mean from incomplete data and for a finite number of counterfactual means can have much higher efficiency than the usual double-robust estimators under misspecification of the outcome model. In this paper, we derive a new class of double-robust estimators for the parameters of regression models with incomplete cross-sectional or longitudinal data, and of marginal structural mean models for cross-sectional data with similar efficiency properties. Unlike the recent proposals, our estimators solve outcome regression estimating equations. In a simulation study, the new estimator shows improvements in variance relative to the standard double-robust estimator that are in agreement with those suggested by asymptotic theory. © 2012 Biometrika Trust. Fil:Sued, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2012 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00063444_v99_n2_p439_Rotnitzky http://hdl.handle.net/20.500.12110/paper_00063444_v99_n2_p439_Rotnitzky
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Drop-out
Marginal structural model
Missing at random
spellingShingle Drop-out
Marginal structural model
Missing at random
Sued, Mariela
Improved double-robust estimation in missing data and causal inference models
topic_facet Drop-out
Marginal structural model
Missing at random
description Recently proposed double-robust estimators for a population mean from incomplete data and for a finite number of counterfactual means can have much higher efficiency than the usual double-robust estimators under misspecification of the outcome model. In this paper, we derive a new class of double-robust estimators for the parameters of regression models with incomplete cross-sectional or longitudinal data, and of marginal structural mean models for cross-sectional data with similar efficiency properties. Unlike the recent proposals, our estimators solve outcome regression estimating equations. In a simulation study, the new estimator shows improvements in variance relative to the standard double-robust estimator that are in agreement with those suggested by asymptotic theory. © 2012 Biometrika Trust.
author Sued, Mariela
author_facet Sued, Mariela
author_sort Sued, Mariela
title Improved double-robust estimation in missing data and causal inference models
title_short Improved double-robust estimation in missing data and causal inference models
title_full Improved double-robust estimation in missing data and causal inference models
title_fullStr Improved double-robust estimation in missing data and causal inference models
title_full_unstemmed Improved double-robust estimation in missing data and causal inference models
title_sort improved double-robust estimation in missing data and causal inference models
publishDate 2012
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00063444_v99_n2_p439_Rotnitzky
http://hdl.handle.net/20.500.12110/paper_00063444_v99_n2_p439_Rotnitzky
work_keys_str_mv AT suedmariela improveddoublerobustestimationinmissingdataandcausalinferencemodels
_version_ 1768546751531188224