Data integration in causal inference

Cites Work

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The prognostic analogue of the propensity score
Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score
Causal inference using invariant prediction: identification and confidence intervals
External validity: from do-calculus to transportability across populations
Statistical data integration in survey sampling: a review
Identification problems and decisions under ambiguity: Empirical analysis of treatment response and normative analysis of treatment choice
Two-sample instrumental variable analyses using heterogeneous samples
Semiparametric efficiency in GMM models with auxiliary data
Semiparametric theory and missing data.
Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials
Bayesian graphical models for regression on multiple data sets with different variables
Robust meta‐analytic‐predictive priors in clinical trials with historical control information
The central role of the propensity score in observational studies for causal effects
Inequalities for E k(X, Y) when the marginals are fixed
Asymptotic Statistics
Nonparametric Estimation of Mean Functionals with Data Missing at Random
Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
Identification, data combination, and the risk of disclosure
Robust Estimation of Encouragement Design Intervention Effects Transported Across Sites
Identifying Treatment Effects Under Data Combination
A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
Adjustment for Missing Confounders Using External Validation Data and Propensity Scores
Doubly Robust Inference when Combining Probability and Non-Probability Samples with High Dimensional Data
Improved methods for moment restriction models with data combination and an application to two‐sample instrumental variable estimation
Combining Multiple Observational Data Sources to Estimate Causal Effects
Generalizing causal inferences from individuals in randomized trials to all trial‐eligible individuals
Regressions, Short and Long
Statistical Matching
Two-sample least squares projection
Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
Safety surveillance and the estimation of risk in select populations: flexible methods to control for confounding while targeting marginal comparisons via standardization
Extending inferences from a randomized trial to a new target population
Causal data fusion methods using summary-level statistics for a continuous outcome
Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization
Generalizing from unrepresentative experiments: a stratified propensity score approach
From sample average treatment effect to population average treatment effect on the treated: combining experimental with observational studies to estimate population treatment effects