Simulation and Hospital Data for Doubly Robust Confidence Intervals

A methodological dataset supporting research on nonparametric inference for causal dose–response curves with continuous treatments. The data, created by Charles R. Doss, includes simulation results and a case study on nurse staffing hours and hospital performance. Supplementary materials for reproducing the work are available.

Use Cases

• Benchmarking doubly robust confidence interval methods based on the described likelihood ratio-type test.
• Studying the effect of monotonicity assumptions on treatment effect curve estimation.
• Evaluating adaptive methods for unknown curve flatness levels mentioned in the description.
• Analyzing the relationship between nurse staffing hours and hospital performance as a practical application.

Strengths

• Includes a 266.1 MB archive of supplementary materials for reproducibility.
• Published under a permissive CC-BY-4.0 license.
• Methodology is described in detail with a specific application to a hospital performance study.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset's primary content appears to be supporting materials for a paper rather than a standalone data collection.

Provenance

Source

Charles R. Doss via figshare

Collection Method

Likely generated from simulations and analysis of a hospital performance dataset, as described in the accompanying research.

Freshness

Last updated 2026-05-21 17:47:42; freshness should be verified.