Kaplan-Meier Report Writer

Kaplan-Meier Report Writer

Turn survival results into a full report

Installed by
3
CategoryResearch
Versionv2
Last updated
Runtime creditsUsage-based
ModelsAuto
FromYouMind

Description

Generates a complete Methods + Results section from your Kaplan-Meier survival curves, log-rank tests, and Cox regression outputs. Correctly interprets hazard ratios, clearly notes when the censoring rate is high, and reminds you to check the proportional hazards assumption for the Cox model. Suitable for researchers working with clinical or epidemiological survival data.

Editor's Recommendation
S

Recommended by

Shuting@YouMind

Why we love this skill

Turns Kaplan-Meier, log-rank, and Cox outputs into complete Methods and Results text while addressing censoring, hazard ratio direction, and proportional hazards assumptions.

Showcase

Related Skills

View all
Research

Logistic Regression ROC-AUC

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.

M
2Free
Research

Group Comparison Test Writer

Produces an APA 7-compliant, publication-ready Results section from your t-test, ANOVA, or chi-square test results. Uses the correct statistical reporting format (t(df)=..., p=..., d=...) and interprets effect sizes according to Cohen’s guidelines. When comparing three or more groups, it reminds you to report the required multiple-comparison correction. Suitable for researchers and graduate students conducting experimental or comparative studies.

M
1Free
Research

Kaplan-Meier Survival Analysis Writer

Produces a complete Methods + Results text from your Kaplan-Meier survival curve, log-rank test, and Cox regression output. Correctly interprets hazard ratios, explicitly flags a high censoring rate, and reminds you to check the proportional hazards assumption for Cox models. Who it's for: researchers working with clinical/epidemiological survival data.

M
3Free

Ready to create something bolder?