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proc-freq-categorical-analysis

Compute measures of association for categorical exposure-outcome data using SAS PROC FREQ.

Updated Jun 11, 2026
Search Tags:#categorical analysis#SAS#PROC FREQ#association measures#stratified analysis
One-click install
npx skills add https://github.com/mrl2013/p8483-and-p8400-assistant --skill proc-freq-categorical-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: proc-freq-categorical-analysis
Source: https://github.com/mrl2013/p8483-and-p8400-assistant/tree/main/.github/skills/proc-freq-categorical-analysis
Command: npx skills add https://github.com/mrl2013/p8483-and-p8400-assistant --skill proc-freq-categorical-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires SAS, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps with analyzing categorical variables in SAS, estimating measures of association (RR, OR, risk difference), and conducting stratified analyses to assess confounding or effect modification.

Core Features & Use Cases

  • Univariate Descriptions: Frequency counts, percentages, and cumulative frequencies.
  • Bivariate Cross-tabulation: Relative risk, odds ratio, risk difference for categorical data analysis.
  • Stratified Analysis: Cochran-Mantel-Haenszel (CMH) summary measures for confounding and effect modification.
  • Use Case: Analyzing categorical data in clinical trials or research studies, such as assessing treatment effects while controlling for confounding variables.

Quick Start

Analyze categorical data with PROC FREQ for exposure and outcome variables in 'mydata'.

Frequently Asked Questions about proc-freq-categorical-analysis

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

FAQPage Schema
How do I calculate odds ratio and risk difference for categorical data in SAS?▼

You can calculate odds ratio and risk difference for categorical data in SAS using PROC FREQ to compute bivariate cross-tabulations and generate exposure-outcome association measures.

How do I perform stratified analysis to control for confounding in SAS?▼

Stratified analysis to control for confounding in SAS is performed using PROC FREQ with Cochran-Mantel-Haenszel summary measures, which assess effect modification across categorical strata.

Do I need SAS to analyze categorical data and compute association measures?▼

Yes, you need SAS installed to run PROC FREQ for categorical data analysis and compute association measures, as this process relies on SAS scripts and appropriate datasets.

What is the best way to assess effect modification in clinical trial categorical data?▼

The best way to assess effect modification in clinical trial categorical data is using SAS PROC FREQ stratified analysis, computing Cochran-Mantel-Haenszel measures to evaluate treatment effects.

Can I generate univariate frequency counts and cumulative percentages using PROC FREQ?▼

Yes, you can generate univariate frequency counts, percentages, and cumulative frequencies using PROC FREQ in SAS to describe individual categorical variables.

Why use stratified analysis instead of standard cross-tabulation for categorical data?▼

Use stratified analysis instead of standard cross-tabulation when you need to control for confounding variables or detect effect modification, which standard bivariate categorical analysis cannot isolate.

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