Logistic Regression ROC-AUC
Interprets logistic regression with ROC-AUC
Logistic Regression ROC-AUC
Interprets logistic regression with ROC-AUC
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Description
Turns your logistic regression analysis outputs (odds ratios, confidence intervals, and ROC-AUC) into an academic Findings section that can be added directly to a paper. Correctly classifies the ROC-AUC value according to standard benchmarks and avoids overstating results for non-significant variables. Suitable for researchers building clinical prediction models and graduate students.
Recommended by
Shuting@YouMind
Why we love this skill
Produces a publication-ready Results section from logistic regression outputs, with clinically accurate odds-ratio interpretation, appropriate caution for nonsignificant variables, and standard ROC-AUC classifications.
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Information
- Version
- v2
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto
