OLS and Quantile Regression Coefficients for Diagnostic Delay Intervention

Ridhima Sodhi's dataset contains estimated regression coefficients from OLS and quantile regression models investigating the impact of an intervention on diagnostic delay. The 9.5 KB XLS file includes coefficient values and their 95% confidence intervals. The dataset was last updated on April 8, 2026.

Use Cases

• Compare OLS and quantile regression coefficient estimates for the intervention variable to understand its central and distributional effects.
• Analyze the 95% confidence intervals for each coefficient to assess the statistical significance of model predictors.
• Use the estimated coefficients to simulate or predict changes in diagnostic delay under different intervention scenarios.

Strengths

• Dataset provides specific statistical outputs (coefficients and confidence intervals) for direct analysis.
• Shared under a permissive CC-BY-4.0 license for reuse.

Limitations

• Extremely small 9.5 KB size suggests the dataset contains only model results, not the underlying raw patient data.
• No underlying sample size, variable definitions, or raw data rows are provided, limiting reproducibility.

Provenance

Source

Ridhima Sodhi via figshare.

Collection Method

Output from statistical regression models (OLS and quantile regression).

Time Range

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Freshness

Last updated in 2026, indicating recent analysis.

Geography

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