Literature DB >> 22462123

Comment: improved local efficiency and double robustness.

Zhiqiang Tan1.   

Abstract

For missing data and causal inference problems, Rubin and van der Laan (2008) proposed estimators to achieve so-called improved local efficiency. We show that their estimators agree with existing estimators in the case of linear models, point out that one particular version of their estimators is also doubly robust, and suggest an extension for where the propensity score is estimated.

Entities:  

Mesh:

Year:  2008        PMID: 22462123     DOI: 10.2202/1557-4679.1109

Source DB:  PubMed          Journal:  Int J Biostat        ISSN: 1557-4679            Impact factor:   0.968


  6 in total

1.  Introduction to Double Robust Methods for Incomplete Data.

Authors:  Shaun R Seaman; Stijn Vansteelandt
Journal:  Stat Sci       Date:  2018       Impact factor: 2.901

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

Authors:  Andrea Rotnitzky; Quanhong Lei; Mariela Sued; James M Robins
Journal:  Biometrika       Date:  2012-04-29       Impact factor: 2.445

3.  Targeted minimum loss based estimator that outperforms a given estimator.

Authors:  Susan Gruber; Mark J van der Laan
Journal:  Int J Biostat       Date:  2012-05-18       Impact factor: 0.968

4.  Improved doubly robust estimation when data are monotonely coarsened, with application to longitudinal studies with dropout.

Authors:  Anastasios A Tsiatis; Marie Davidian; Weihua Cao
Journal:  Biometrics       Date:  2010-08-19       Impact factor: 2.571

5.  Rejoinder to comments on Evaluation of Viable Dynamic Treatment Regimes in a Sequentially Randomized Trial of Advanced Prostate Cancer.

Authors:  Lu Wang; Andrea Rotnitzky; Xihong Lin; Randall E Millikan; Peter F Thall
Journal:  J Am Stat Assoc       Date:  2012       Impact factor: 5.033

6.  Semiparametric tests for sufficient cause interaction.

Authors:  Stijn Vansteelandt; Tyler J VanderWeele; James M Robins
Journal:  J R Stat Soc Series B Stat Methodol       Date:  2012-03       Impact factor: 4.488

  6 in total

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