Biostatistics Analysis Tool

Automate survival analysis, logistic regression, ROC analysis, and sample size calculations on clinical datasets.

9|2|Updated Mar 3, 2026

Search Tags:#data-analysis #survival-analysis #clinical-research #roc-analysis #biostatistics #logistic-regression #sample-size-calculation

Ready to run

npx skills add https://github.com/gitjfmd/open-medical-skills --skill biostatistics-analysis-tool

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Biostatistics Analysis Tool
Source: https://github.com/gitjfmd/open-medical-skills/tree/main/skills/biostatistics-analyzer
Command: npx skills add https://github.com/gitjfmd/open-medical-skills --skill biostatistics-analysis-tool

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates biostatistical analyses on clinical datasets to speed up medical research workflows and reduce manual calculation errors.

Core Features & Use Cases

Survival analysis with Kaplan-Meier or Cox models to evaluate time-to-event data.
Logistic regression and ROC analysis to assess predictive performance.
Sample size and power calculations to plan studies and determine required enrollment.
Use Case: A clinical research team wants to compare time-to-event outcomes between two cohorts and quantify model discrimination.

Quick Start

Provide a CSV file containing patient data and request a complete biostatistical analysis, including survival curves, regression results, and ROC metrics.

Frequently Asked Questions about Biostatistics Analysis Tool

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I perform survival analysis on a clinical dataset with time-to-event data?▼

Survival analysis on clinical datasets is performed using Kaplan-Meier or Cox models to evaluate time-to-event outcomes. Provide a CSV file with patient data to compute survival curves and quantify cohort differences.

What is the best way to calculate sample size and power for a medical research study?▼

Sample size and power calculations plan studies and determine required enrollment numbers. Automating biostatistical analyses validates inputs and computes these metrics to ensure your clinical research study is adequately powered.

How do I run logistic regression and ROC analysis to assess predictive performance?▼

Logistic regression and ROC analysis assess predictive performance by computing discrimination metrics. Provide clinical patient data in a CSV format to generate regression results and ROC curves to validate model performance.

Can I use a CSV file to automate biostatistics analyses across multiple medical research scenarios?▼

Yes, CSV files containing patient data can automate biostatistics analyses across medical research scenarios. The process validates inputs, selects appropriate models, computes outputs, and provides interpretable results with basic diagnostics.

Does the biostatistics analysis provide diagnostics for survival and regression models?▼

Biostatistics analysis provides interpretable results with basic diagnostics for survival and regression models. It validates inputs, selects appropriate models, and computes outputs to reduce manual calculation errors in clinical datasets.