Applied Ordinal Logistic Regression Using Stata (ULTIMATE ✓)

: This article on PMC demonstrates using ordinal logistic regression to determine household socioeconomic factors, explicitly recommending the use of partial proportional odds models (PPOM) when covariates violate proportionality. Quick Reference Guides

While there are several excellent papers and guides, the definitive core resource on this topic is actually a textbook: by Xing Liu (2016) . Applied Ordinal Logistic Regression Using Stata

: A practical application found on ScienceDirect uses proportional and partial proportional odds models to classify household energy usage, providing a clear roadmap for reporting results. : This article on PMC demonstrates using ordinal

If you specifically need shorter, peer-reviewed papers that demonstrate the application or technical nuances in Stata, consider these options: Technical & Comparative Papers If you specifically need shorter, peer-reviewed papers that

: For a fast, tutorial-style "paper," the UCLA Stata Data Analysis Examples provide code snippets, output interpretation, and step-by-step guidance for running ologit . Applied Ordinal Logistic Regression Using Stata

: For cases where the proportional odds assumption is violated, the seminal paper on the gologit2 command by Richard Williams (2006) is the industry standard for learning how to fit partial proportional odds models in Stata. Applied Research Examples