ordinal-multinomial-logistic-regression
CommunityAnalyze outcomes with multiple categories using proportional odds or multinomial logistic regression.
Data & Analytics#logistic regression#outcome analysis#categorical analysis#proportional odds#multinomial
Authormrl2013
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps analyze outcomes with multiple categories, whether ordered or unordered, using proportional odds or multinomial logistic regression, suitable when linear regression assumptions are not met.
Core Features & Use Cases
- Proportional Odds Logistic Regression: For ordered outcomes with proportional odds, estimates cumulative odds per unit increase in a predictor.
- Multinomial Logistic Regression: For unordered outcomes, runs a series of binary logistic regressions against a common reference category.
- Use Case: When analyzing patient treatment effectiveness with multiple severity grades, proportional odds regression can be used to assess the impact of treatment on severity levels.
Quick Start
Use the ordinal-multinomial-logistic-regression skill to fit a proportional odds model for the 'severity' outcome variable.
Dependency Matrix
Required Modules
SASR
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: ordinal-multinomial-logistic-regression Download link: https://github.com/mrl2013/p8483-and-p8400-assistant/archive/main.zip#ordinal-multinomial-logistic-regression Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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