Ordinal Logistic Regression with Jamovi

Analyzing survey scales, Likert data, and ranked outcomes requires statistical techniques designed specifically for ordered categories. This text-based course guides you through conducting, evaluating, and interpreting ordinal logistic regression models using the modern, user-friendly Jamovi interface. You will start with foundational statistical concepts and progress toward building reliable predictive models and clearly reporting your results. What you will learn: Understand the mathematical foundations of ordinal variables, cumulative logit links, and odds ratios. Configure and execute ordinal logistic regression models step by step in Jamovi. Test and validate key model assumptions, including the proportional odds assumption. Interpret model coefficients, threshold parameters, and goodness-of-fit indicators such as AIC, BIC, and pseudo R-squared values. Apply modern reporting standards to present statistical output clearly for research papers and reports. The course opens with essential terminology and statistical definitions before walking through practical model specifications and diagnostic workflows. Designed for beginners, researchers, and students, no prior advanced regression experience is required. Start reading today to build confidence in analyzing ordered categorical data.