Episode 25: The Proportional Odds Assumption in Clinical Trials

In this QCast episode, Jullia and Tom unpack the proportional odds assumption in ordinal logistic regression, explaining what it means in practice, why it matters for ordinal endpoints in clinical trials, and how to diagnose and handle violations without losing the value of ordered scales.Key TakeawaysUnderstand that proportional odds implies a single treatment effect across all cut points of an ordered endpoint, enabling an efficient summary of benefit.Examine outcome distributions, use formal tests, and compare treatment effects across thresholds to assess whether the assumption is reasonable.Plan for alternatives such as partial proportional odds or more flexible models, and document the rationale so methods and interpretations remain transparent to clinicians and regulators.🔗 Learn More & Get Support: Visit quanticate.com to explore our biometrics services and discover how we can support your next clinical trial. 📝 Episode Notes & Transcript: Find show notes, resources, and a full transcript at quanticate.com/podcast.🔔 Stay Connected: Subscribe to QCast on Apple Podcasts, Spotify, or your favourite platform to never miss an episode.About QuanticateFounded in 1994, Quanticate is a biometrics-focused CRO with over 30 years' experience delivering expert clinical and post-marketing data services worldwide. Specialising in the collection, management, standardisation, analysis, and reporting of data, we support pharma and biotech companies globally with high-quality solutions for clinical development. We specialise in:Clinical Data Capture & ManagementBiostatistics & Statistical ConsultancyStatistical Programming & PK/PD AnalysisMedical Writing & PharmacovigilanceRegulatory & Submission SupportAI & AutomationPost-Marketing Safety & Real-World DataQuanticate is committed to delivering expertise and solutions that drive the success of clinical development worldwide.