skills.rest
KangWang42
KangWang42COMMUNITY
Explore all skills by this author →
GitHub

r-biostats

Provides epidemiological and biostatistical analysis in R, including Cox regression and survival curves.

14|2|Updated Jan 29, 2026
Search Tags:#data analysis#statistics#regression#r#survival analysis#epidemiology#biostatistics
One-click install
npx skills add https://github.com/KangWang42/EpiClaude --skill r-biostats
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: r-biostats
Source: https://github.com/KangWang42/EpiClaude/tree/main/skills/r-biostats
Command: npx skills add https://github.com/KangWang42/EpiClaude --skill r-biostats

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines complex epidemiological and biostatistical analyses using R, addressing the need for specialized statistical modeling, data visualization, and reporting in medical research.

Core Features & Use Cases

  • Statistical Analysis: Perform descriptive statistics, regression (linear, logistic, Poisson), survival analysis (Kaplan-Meier, Cox), mediation/moderation, and meta-analysis.
  • Data Visualization: Generate publication-quality plots with scientific color palettes and proper formatting.
  • Reporting: Create standardized tables (e.g., Table 1) and summarize results for reports and papers.
  • Use Case: Analyze a cohort study dataset to investigate the relationship between lifestyle factors and cardiovascular events using Cox regression, generating survival curves and a summary table of results.

Quick Start

Use the r-biostats skill to perform a Cox regression analysis on the dataset 'my_data.csv' to examine the association between 'exposure' and 'outcome', adjusting for 'age' and 'sex'.

Frequently Asked Questions about r-biostats

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

FAQPage Schema
How do I perform Cox regression and survival analysis in R for a cohort study?▼

Cox regression and survival analysis in R can be performed to examine associations between exposures and outcomes, adjusting for covariates like age and sex. This approach generates survival curves and summary tables for medical research.

Can I generate publication-quality plots and standardized tables for epidemiology research?▼

Publication-quality plots and standardized tables like Table 1 can be generated for epidemiology research using R. This process utilizes scientific color palettes and proper formatting to summarize descriptive statistics and regression results for reports.

What is the best way to run mediation effects and meta-analysis in R?▼

Mediation effects and meta-analysis in R are best executed through functional programming and standardized output formats. This ensures reproducible research when investigating direct and indirect effects across multiple medical studies.

Does this biostatistics approach support logistic and Poisson regression for public health data?▼

This biostatistics approach supports logistic and Poisson regression for public health data alongside linear modeling. It facilitates comprehensive statistical analysis while adhering to strict coding principles for data cleaning and reproducible reporting.

How to ensure reproducible research when doing data cleaning and visualization in R?▼

Reproducible research during data cleaning and visualization in R is ensured by adhering to strict coding principles including relative paths and functional programming. This standardizes output formats for epidemiological and biostatistical analyses.

Related Skills

Explore More Education & Research Skills→
AperivueAperivue
243

clean-data

Profile clinical CSV/Excel datasets and generate reproducible cleaning scripts.

Official
Advanced
Estrella-231Estrella-231

scientific-visualization

Generate publication-ready matplotlib/seaborn figures with journal-specific styles and export settings.

Community
Intermediate
mgaldinomgaldino
5

compile-rmd

Render RMarkdown documents into PDF, HTML, or Bookdown formats.

Community
Intermediate
mrl2013mrl2013

effect-measure-modification

Analyze interaction effects in regression models to detect modification by a third variable.

Community
Advanced