cross-national

Harmonize variables across KNHANES, NHANES, and CHNS for parallel weighted analyses.

243|60|Updated Apr 6, 2026
One-click install
npx skills add https://github.com/Aperivue/medsci-skills --skill cross-national
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cross-national
Source: https://github.com/Aperivue/medsci-skills/tree/main/skills/cross-national
Command: npx skills add https://github.com/Aperivue/medsci-skills --skill cross-national

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

End-to-end cross-national health research requires harmonizing variables across diverse surveys and performing parallel weighted analyses to enable fair comparisons.

Core Features & Use Cases

  • Harmonization of variables across KNHANES, NHANES, and CHNS to enable comparable analyses.
  • Parallel country-specific weighted analyses respecting survey design and country-specific BMI/SES cutoffs.
  • Generation of cross-national comparison tables and study protocols suitable for manuscripts and reports.

Quick Start

Run a harmonized cross-national analysis pipeline on KNHANES and NHANES (and CHNS if available) to compare exposure–outcome associations across Korea, the US, and China.

Frequently Asked Questions about cross-national

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

FAQPage Schema
How do I harmonize NHANES and KNHANES survey data for cross-national comparison?▼

Cross-national survey harmonization aligns variables across NHANES and KNHANES by applying country-specific BMI and SES cutoffs alongside separate survey designs, producing comparable datasets for parallel weighted analysis.

Can I compare health outcomes across Korea, the US, and China using KNHANES, NHANES, and CHNS?▼

Yes, you can compare health outcomes across Korea, the US, and China by harmonizing KNHANES, NHANES, and CHNS variables and executing parallel country-specific weighted analyses to ensure valid cross-national comparisons.

What is the best way to apply country-specific BMI cutoffs in a three-country survey analysis?▼

The best way to apply country-specific BMI cutoffs in a three-country survey analysis is to use a harmonization pipeline that sets distinct thresholds for Korea, the US, and China while maintaining identical analytic specifications across countries.

Does this cross-national analysis approach support generating manuscript-ready tables and protocols?▼

Yes, this cross-national analysis approach supports generating manuscript-ready tables and study protocols by documenting harmonization decisions and executing parallel weighted analyses across KNHANES, NHANES, and CHNS datasets.

Why do I need separate survey designs for Korea, the United States, and China in cross-national research?▼

You need separate survey designs for Korea, the United States, and China because each national survey has distinct sampling structures. Respecting these designs ensures accurate weighted analysis and valid cross-national exposure-outcome comparisons.

How do I document harmonization decisions for SES variables across NHANES and CHNS?▼

To document harmonization decisions for SES variables across NHANES and CHNS, you execute a harmonization pipeline that explicitly records variable alignment choices and applies country-specific cutoffs to generate transparent study protocols.