Sharpening the Rosenbaum Sensitivity Bounds to Address Concerns About Interactions Between Observed and Unobserved Covariates

@article{Heng2020SharpeningTR,
  title={Sharpening the Rosenbaum Sensitivity Bounds to Address Concerns About Interactions Between Observed and Unobserved Covariates},
  author={Siyu Heng and Dylan S. Small},
  journal={arXiv: Methodology},
  year={2020}
}
In observational studies, it is typically unrealistic to assume that treatments are randomly assigned, even conditional on adjusting for all observed covariates. Therefore, a sensitivity analysis is often needed to examine how hidden biases due to unobserved covariates would affect inferences on treatment effects. In matched observational studies where each treated unit is matched to one or multiple untreated controls for observed covariates, the Rosenbaum bounds sensitivity analysis is one of… 

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SHOWING 1-10 OF 58 REFERENCES
Sensitivity analysis for certain permutation inferences in matched observational studies
SUMMARY In observational studies, treatments are not randomly assigned to experimental units, so that randomization tests and their associated interval estimates are not generally applicable. In an
Studentized Sensitivity Analysis for the Sample Average Treatment Effect in Paired Observational Studies
Abstract A fundamental limitation of causal inference in observational studies is that perceived evidence for an effect might instead be explained by factors not accounted for in the primary
Calibrating Sensitivity Analyses to Observed Covariates in Observational Studies
TLDR
This work proposes an approach that calibrates the values of the sensitivity parameters to the observed covariates and is more interpretable to subject matter experts and will illustrate the method using data from the U.S. National Health and Nutrition Examination Survey regarding the relationship between cigarette smoking and blood lead levels.
Extended sensitivity analysis for heterogeneous unmeasured confounding with an application to sibling studies of returns to education
The conventional model for assessing insensitivity to hidden bias in paired observational studies constructs a worst-case distribution for treatment assignments subject to bounds on the maximal bias
Amplification of Sensitivity Analysis in Matched Observational Studies
TLDR
A sensitivity analysis displays the increase in uncertainty that attends an inference when a key assumption is relaxed and an amplification of a sensitivity analysis is defined as a map from each point in a low-dimensional sensitivity analysis to a set of points in a higher dimensional sensitivity analysis such that the possible inferences are the same for all points in the set.
Sensitivity Analysis for Multiple Comparisons in Matched Observational Studies Through Quadratically Constrained Linear Programming
ABSTRACT A sensitivity analysis in an observational study assesses the robustness of significant findings to unmeasured confounding. While sensitivity analyses in matched observational studies have
7. Assessing Bias in the Estimation of Causal Effects: Rosenbaum Bounds on Matching Estimators and Instrumental Variables Estimation with Imperfect Instruments
Propensity score matching provides an estimate of the effect of a “treatment” variable on an outcome variable that is largely free of bias arising from an association between treatment status and
Model assisted sensitivity analyses for hidden bias with binary outcomes
TLDR
This work proposes a model assisted sensitivity analysis with binary outcomes for the general 1:k matching design, which provides results equivalent to the conventional nonparametric approach in large sample by introducing a conditional logistic outcome model.
Strong Control of the Familywise Error Rate in Observational Studies that Discover Effect Modification by Exploratory Methods
An effect modifier is a pretreatment covariate that affects the magnitude of the treatment effect or its stability. When there is effect modification, an overall test that ignores an effect modifier
Split Samples and Design Sensitivity in Observational Studies
An observational or nonrandomized study of treatment effects may be biased by failure to control for some relevant covariate that was not measured. The design of an observational study is known to
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