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Establishing cause-effect relationships from observational data often relies on untestable assumptions.
Smoking and lung cancer: recent evidence and a discussion of some questions
Cornfield, J., Haenszel, W., Hammond, E. C., Lilienfeld, A. M., Shimkin, M. B., and Wynder, E. L. (1959) · 1959
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Estimating causal effects of treatments in randomized and non-randomized studies
Rubin, D. B. (1974) · 1974
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A new approach to causal inference in mortality studies with sustained exposure periods – application to control of the healthy worker survivor effect
Robins, J. M. (1986) · 1986
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Minimax estimation of a functional on a structured high-dimensional model
Robins, J. M., Li, L., Mukherjee, R., Tchetgen, E. T., van der Vaart, A., et al. (2017) · 1987
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Sensitivity analysis for certain permutation inferences in matched observational studies
Rosenbaum, P. R. (1987) · 1987
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The analysis of randomized and non-randomized aids treatment trials using a new approach to causal inference in longitudinal studies
Robins, J. M. (1989) · 1989
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Nonparametric bounds on treatment effects
Manski, C. F. (1990) · 1990
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Sur les applications de la thar des probabilities aux experiences agaricales: Essay des principle. excerpts reprinted (1990) in English
Neyman, J. (1923) · 1990
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Estimation of regression coefficients when some regressors are not always observed
Robins, J. M., Rotnitzky, A., and Zhao, L. P. (1994) · 1994
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The very low birthweight infant: maternal complications leading to preterm birth, placental lesions, and intrauterine growth
Salafia, C. M., Ernst, L. M., Pezzullo, J. C., Wolf, E. J., Rosenkrantz, T. S., and Vintzileos, A. M. (1995) · 1995
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Intrauterine growth restriction in infants of less than thirty-two weeks’ gestation: associated placental pathologic features
Salafia, C. M., Minior, V. K., Pezzullo, J. C., Popek, E. J., Rosenkrantz, T. S., and Vintzileos, A. M. (1995) · 1995
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Fetal macrosomia: risk factors and outcome: A study of the outcome concerning 100 cases > > 4500 g
Berard, J., Dufour, P., Vinatier, D., Subtil, D., Vanderstichele, S., Monnier, J., and Puech, F. (1998) · 1998
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Dual and simultaneous sensitivity analysis for matched pairs
Gastwirth, J. L., Krieger, A. M., and Rosenbaum, P. R. (1998) · 1998
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Association, causation, and marginal structural models
Robins, J. M. (1999) · 1999
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Adjusting for nonignorable drop-out using semiparametric nonresponse models
Scharfstein, D. O., Rotnitzky, A., and Robins, J. M. (1999) · 1999
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Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models
Robins, J. M., Rotnitzky, A., and Scharfstein, D. O. (2000) · 2000
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Sensitivity to exogeneity assumptions in program evaluation
Imbens, G. W. (2003) · 2003
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Generalized additive selection models for the analysis of studies with potentially nonignorable missing outcome data
Scharfstein, D. O. and Irizarry, R. A. (2003) · 2003
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Influence of maternal tobacco smoking during pregnancy on uterine, umbilical and fetal cerebral artery blood flows
Albuquerque, C. A., Smith, K. R., Johnson, C., Chao, R., and Harding, R. (2004) · 2004
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Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures
Brumback, B. A., Hernán, M. A., Haneuse, S. J., and Robins, J. M. (2004) · 2004
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Nonparametric estimation of an additive model with a link function
Horowitz, J. L., Mammen, E., et al. (2004) · 2004
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Risk factors and obstetric complications associated with macrosomia
Stotland, N., Caughey, A., Breed, E., and Escobar, G. (2004) · 2004
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The costs of low birth weight
Almond, D., Chay, K. Y., and Lee, D. S. (2005) · 2005
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Estimating causal effects from epidemiological data
Hernán, M. A. and Robins, J. M. (2006) · 2006
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Identification of joint interventional distributions in recursive semi-Markovian causal models
Shpitser, I. and Pearl, J. (2006) · 2006
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A distributional approach for causal inference using propensity scores
Tan, Z. (2006) · 2006
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Semiparametric Theory and Missing Data
Tsiatis, A. A. (2006) · 2006
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Generalized Additive Models
Hastie, T. J. and Tibshirani, R. J. (2017) · 2017
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An effective semiparametric estimation approach for the sufficient dimension reduction model
Huang, M.-Y. and Chiang, C.-T. (2017) · 2017
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Sensitivity analysis
Díaz, I., Luedtke, A. R., and van der Laan, M. J. (2018) · 2018
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Subclinical and clinical chorioamnionitis, fetal vasculitis, and risk for preterm birth: A cohort study
Palmsten, K., Nelson, K. K., Laurent, L. C., Park, S., Chambers, C. D., and Parast, M. M. (2018) · 2018
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Bounds on the conditional and average treatment effect with unobserved confounding factors
Yadlowsky, S., Namkoong, H., Basu, S., Duchi, J., and Tian, L. (2018) · 2018
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Targeted maximum likelihood learning
van Der Laan, M. J. and Rubin, D. (2006) · 2006
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Super learner
van der Laan, M. J., Polley, E. C., and Hubbard, A. E. (2007) · 2007
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Higher order influence functions and minimax estimation of nonlinear functionals
Robins, J., Li, L., Tchetgen, E., van der Vaart, A., et al. (2008) · 2008
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Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · 2009
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Sensitivity analysis for causal inference using inverse probability weighting
Shen, C., Li, X., Li, L., and Were, M. C. (2011) · 2011
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Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders
VanderWeele, T. J. and Arah, O. A. (2011) · 2011
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Zhao, Q., Small, D. S., and Bhattacharya, B. B. (2019) · 2019
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Making sense of sensitivity: Extending omitted variable bias
Cinelli, C. and Hazlett, C. (2020) · 2020
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Flexible sensitivity analysis for observational studies without observable implications
Franks, A., D’Amour, A., and Feller, A. (2020) · 2020
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Sense and sensitivity analysis: Simple post-hoc analysis of bias due to unobserved confounding
Veitch, V. and Zaveri, A. (2020) · 2020
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Doubly-valid/doubly-sharp sensitivity analysis for causal inference with unmeasured confounding
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Characterization of parameters with a mixed bias property
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A new principle for tuning-free huber regression
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Semiparametric inference for causal effects in graphical models with hidden variables
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Sensitivity analysis via the proportion of unmeasured confounding
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Sharp sensitivity analysis for inverse propensity weighting via quantile balancing
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Semiparametric doubly robust targeted double machine learning: a review
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Sensitivity analysis for causal effects with generalized linear models
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A semi-parametric approach to model-based sensitivity analysis in observational studies
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