A pilot design for observational studies: using abundant data thoughtfully
From MaRDI portal
Publication:6617428
DOI10.1002/sim.8754zbMATH Open1546.62046MaRDI QIDQ6617428
Dylan Greaves, Unnamed Author, Unnamed Author
Publication date: 10 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
matchingobservational studiescausal inferencepropensity scoreprognostic scoreassignment-control plots
Cites Work
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- Doubly Robust Estimation in Missing Data and Causal Inference Models
- The prognostic analogue of the propensity score
- Matching methods for causal inference: a review and a look forward
- For objective causal inference, design trumps analysis
- Two-sample instrumental variable analyses using heterogeneous samples
- The central role of the propensity score in observational studies for causal effects
- Relaxation Methods for Minimum Cost Ordinary and Generalized Network Flow Problems
- Asymptotic Statistics
- Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
- Split Samples and Design Sensitivity in Observational Studies
- Large Sample Properties of Matching Estimators for Average Treatment Effects
- Sensitivity Analysis for m‐Estimates, Tests, and Confidence Intervals in Matched Observational Studies
- Full Matching in an Observational Study of Coaching for the SAT
Related Items (4)
Practical recommendations on double score matching for estimating causal effects ⋮ Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score ⋮ Comment on ``Protocols for observational studies ⋮ Rejoinder: Protocols for observational studies: methods and open problems
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