articleTop 10% cited
Assessing Sensitivity to an Unobserved Binary Covariate in an Observational Study with Binary Outcome
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1983 · Vol. 45(2) · pp. 212–218
Peter Rosenbaum✉(University of Wisconsin–Madison)Donald B. Rubin(University of Wisconsin–Madison)
Abstract
SUMMARY This paper proposes a simple technique for assessing the range of plausible causal conclusions from observational studies with a binary outcome and an observed categorical covariate. The technique assesses the sensitivity of conclusions to assumptions about an unobserved binary covariate relevant to both treatment assignment and response. A medical study of coronary artery disease is used to illustrate the technique.
Advanced Causal Inference TechniquesStatistical Methods and Bayesian InferenceStatistical Methods in Clinical TrialsCovariateCategorical variableObservational studyOutcome (game theory)Binary numberStatisticsEconometricsBinary dataSensitivity (control systems)Mathematics
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References
Conditional Independence in Statistical Theory
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1979 · 1,517 citations
Design of Experiments
BMJ · 1936 · 4,217 citations
Bayesian Inference for Causal Effects: The Role of Randomization
The Annals of Statistics · 1978 · 2,510 citations
The central role of the propensity score in observational studies for causal effects
Biometrika · 1983 · 30,427 citations
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