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To identify the estimand in missing data problems and observational studies, it is common to base the statistical estimation on the "missing at random" and "no unmeasured confounder" assumptions.
Maximization of a linear function of variables subject to linear inequalities
George B Dantzig · 1951
Earlier work this paper cites.
A generalization of sampling without replacement from a finite universe
Daniel G Horvitz and Donovan J Thompson · 1952
Earlier work this paper cites.
Cigarettes, cancer and statistics
Ronald A Fisher · 1958
Earlier work this paper cites.
Smoking and lung cancer: recent evidence and a discussion of some questions
Jerome Cornfield, William Haenszel, E Cuyler Hammond, Abraham M Lilienfeld, Michael B Shimkin, and Ernst L Wynder · 1959
Earlier work this paper cites.
Programming with linear fractional functionals
Abraham Charnes and William W Cooper · 1962
Earlier work this paper cites.
Estimates of location based on rank tests
Joseph L Jr Hodges and Erich L Lehmann · 1963
Earlier work this paper cites.
Estimating causal effects of treatments in randomized and nonrandomized studies
Donald B Rubin · 1974
Earlier work this paper cites.
Inference and missing data
Donald B Rubin · 1976
Earlier work this paper cites.
Bootstrap methods: Another look at the jackknife
Bradley Efron · 1979
Earlier work this paper cites.
Comment on “Randomization analysis of experimental data: The fisher randomization test”
Donald B Rubin · 1980
Earlier work this paper cites.
The central role of the propensity score in observational studies for causal effects
Paul R Rosenbaum and Donald B Rubin · 1983
Earlier work this paper cites.
Sensitivity analysis for certain permutation inferences in matched observational studies
Paul R Rosenbaum · 1987
Earlier work this paper cites.
Vitamin A and lung cancer
Walter C Willett · 1990
Earlier work this paper cites.
An introduction to the bootstrap
Bradley Efron and Robert J Tibshirani · 1994
Earlier work this paper cites.
Estimation of regression coefficients when some regressors are not always observed
James M Robins, Andrea Rotnitzky, and Lue Ping Zhao · 1994
Earlier work this paper cites.
The effect of vitamin E and beta carotene on the incidence of lung cancer and other cancers in male smokers
The Alpha-Tocopherol Beta Carotene Cancer Prevention Study Group · 1994
Earlier work this paper cites.
Bootstrapping
J. A. Wellner and Yihui Zhan · 1996
Earlier work this paper cites.
Dual and simultaneous sensitivity analysis for matched pairs
Joseph L Gastwirth, Abba M Krieger, and Paul R Rosenbaum · 1998
Earlier work this paper cites.
Association, causation, and marginal structural models
James M Robins · 1999
Earlier work this paper cites.
Adjusting for nonignorable drop-out using semiparametric nonresponse models
Daniel O Scharfstein, Andrea Rotnitzky, and James M Robins · 1999
Earlier work this paper cites.
Comment on “covariance adjustment in randomized experiments and observational studies”
James M Robins · 2002
Earlier work this paper cites.
Pattern-mixture and selection models for analysing longitudinal data with monotone missing patterns
Jolene Birmingham, Andrea Rotnitzky, and Garrett M Fitzmaurice · 2003
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Sensitivity analysis for the assessment of causal vaccine effects on viral load in hiv vaccine trials
Peter B Gilbert, Ronald J Bosch, and Michael G Hudgens · 2003
Cited alongside, same era.
Efficient estimation of average treatment effects using the estimated propensity score
Keisuke Hirano, Guido W Imbens, and Geert Ridder · 2003
Cited alongside, same era.
Sensitivity to exogeneity assumptions in program evaluation
Guido W Imbens · 2003
Cited alongside, same era.
Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures
Babette A Brumback, Miguel A Hernán, Sebastien JPA Haneuse, and James M Robins · 2004
Cited alongside, same era.
Missing data in longitudinal studies: Strategies for Bayesian modeling and sensitivity analysis
Michael J Daniels and Joseph W Hogan · 2008
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Targeted learning: causal inference for observational and experimental data
Mark J Van der Laan and Sherri Rose · 2011
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Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders
Tyler J VanderWeele and Onyebuchi A Arah · 2011
Later among the works it cites.
Interval estimation of population means under unknown but bounded probabilities of sample selection
Peter M Aronow and Donald KK Lee · 2012
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The prevention and treatment of missing data in clinical trials
Roderick J Little, Ralph D’agostino, Michael L Cohen, Kay Dickersin, Scott S Emerson, John T Farrar, Constantine Frangakis, Joseph W Hogan, Geert Molenberghs, Susan A Murphy, et al · 2012
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Confidence intervals for partially identified parameters
Guido W Imbens and Charles F Manski · 2004
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Those confounded vitamins: what can we learn from the differences between observational versus randomised trial evidence?
Debbie A Lawlor, George Davey Smith, K Richard Bruckdorfer, Devi Kundu, and Shah Ebrahim · 2004
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Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study
Jared K Lunceford and Marie Davidian · 2004
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Selection on observed and unobserved variables: Assessing the effectiveness of catholic schools
Joseph G Altonji, Todd E Elder, and Christopher R Taber · 2005
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Empirical Processes: Theory and Applications
Jon A. Wellner · 2005
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Causal vaccine effects on binary postinfection outcomes
Michael G Hudgens and M Elizabeth Halloran · 2006
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Introduction to Empirical Processes and Semiparametric Inference
Michael R. Kosorok · 2006
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Generalized minimax and maximin inequalities for order statistics and quantile functions
Joel E Cohen · 2013
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Sensitivity analysis of per-protocol time-to-event treatment efficacy in randomized clinical trials
Peter B Gilbert, Bryan E Shepherd, and Michael G Hudgens · 2013
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Inference on treatment effects after selection among high-dimensional controls
Alexandre Belloni, Victor Chernozhukov, and Christian Hansen · 2014
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Statistical analysis with missing data
Roderick JA Little and Donald B Rubin · 2014
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Nonparametric bounds and sensitivity analysis of treatment effects
Amy Richardson, Michael G Hudgens, Peter B Gilbert, and Jason P Fine · 2014
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Two R packages for sensitivity analysis in observational studies
Paul R Rosenbaum · 2015
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Approximate residual balancing: De-biased inference of average treatment effects in high dimensions
Susan Athey, Guido W Imbens, and Stefan Wager · 2016
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Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis
Peter C Austin · 2016
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Sensitivity analysis without assumptions
Peng Ding and Tyler J VanderWeele · 2016
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Double/debiased machine learning for treatment and structural parameters
Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney Newey, and James Robins · 2017
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A paradox from randomization-based causal inference
Peng Ding · 2017
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Colin B Fogarty · 2017
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Randomization inference and sensitivity analysis for composite null hypotheses with binary outcomes in matched observational studies
Colin B Fogarty, Pixu Shi, Mark E Mikkelsen, and Dylan S Small · 2017
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Shape-constrained partial identification of a population mean under unknown probabilities of sample selection
Luke W Miratrix, Stefan Wager, and Jose R Zubizarreta · 2017
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Cross-screening in observational studies that test many hypotheses
Qingyuan Zhao, Dylan S Small, and Paul R Rosenbaum · 2017
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