A pilot design for observational studies: using abundant data thoughtfully

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)

zbMATH Keywords

matchingobservational studiescausal inferencepropensity scoreprognostic scoreassignment-control plots

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Unnamed Item
• Unnamed Item
• 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

This page was built for publication: A pilot design for observational studies: using abundant data thoughtfully