Protocols for observational studies: methods and open problems

Cites Work

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Testing one hypothesis twice in observational studies
Instrumental variables: an econometrician's perspective
Matching methods for causal inference: a review and a look forward
Recursive partitioning and applications
The sensitivity of linear regression coefficients' confidence limits to the omission of a confounder
Association and probability inequalities
Choice as an alternative to control in observational studies. (With comments and a rejoinder).
False discovery rate control for effect modification in observational studies
Covariance adjustment in radomized experiments and observational studies
On the definition of a confounder
Assessment of the extent of corroboration of an elaborate theory of a causal hypothesis using partial conjunctions of evidence factors
Bayesian regression tree models for causal inference: regularization, confounding, and heterogeneous effects (with discussion)
The information in covariate imbalance in studies of hormone replacement therapy
Matching methods for observational studies derived from large administrative databases
An exact adaptive test with superior design sensitivity in an observational study of treatments for ovarian cancer
Using Multivariate Matched Sampling and Regression Adjustment to Control Bias in Observational Studies
Amplification of Sensitivity Analysis in Matched Observational Studies
Using Split Samples and Evidence Factors in an Observational Study of Neonatal Outcomes
Quantiles in Nonrandom Samples and Observational Studies
Strong control of the familywise error rate in observational studies that discover effect modification by exploratory methods
Statistical inference for exploratory data analysis and model diagnostics
Testing hypotheses in order
The central role of the propensity score in observational studies for causal effects
A note on data-splitting for the evaluation of significance levels
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
Effect Modification and Design Sensitivity in Observational Studies
Clustered Treatment Assignments and Sensitivity to Unmeasured Biases in Observational Studies
Discovering Heterogeneous Exposure Effects Using Randomization Inference in Air Pollution Studies
Increasing Power for Observational Studies of Aberrant Response: An Adaptive Approach
Double/debiased machine learning for treatment and structural parameters
Making Sense of Sensitivity: Extending Omitted Variable Bias
Covariate selection strategies for causal inference: Classification and comparison
Split Samples and Design Sensitivity in Observational Studies
Causal Inference for Statistics, Social, and Biomedical Sciences
An adaptive Mantel–Haenszel test for sensitivity analysis in observational studies
A Method to Increase the Power of Multiple Testing Procedures Through Sample Splitting
Design sensitivity in observational studies
Matching and thick description in an observational study of mortality after surgery
Full Matching in an Observational Study of Coaching for the SAT
Selecting and Ranking Individualized Treatment Rules With Unmeasured Confounding
Sensitivity Analysis via the Proportion of Unmeasured Confounding
Design of observational studies
Observational studies.
Discussion: ``A significance test for the lasso
A New Transformation of Treated-Control Matched-Pair Differences for Graphical Display
Commentary on: ``Randomization: the forgotten component of the randomized clinical trial
A method to aid statistical judgment on outliers: comment on Hill's ``The statistician in medicine
Confounder selection strategies targeting stable treatment effect estimators
A calibrated sensitivity analysis for matched observational studies with application to the effect of second-hand smoke exposure on blood lead levels in children