Related Experiment Video
Updated: Jan 7, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Primer for Clinical Researchers on Ordinal Outcomes for Emergency Medicine
Chris J Selman1, Sean W X Ong2,3,4,5, Melissa Middleton1,6
1Clinical Epidemiology and Biostatistics Unit, Murdoch Children's Research Institute, Parkville, Australia.
Ordinal outcomes offer a flexible way to measure treatment effects in clinical research. This overview explains their use in emergency medicine, including statistical methods for better understanding.
Area of Science:
- Clinical Research
- Biostatistics
- Emergency Medicine
Background:
- Ordinal outcomes are increasingly utilized in clinical research.
- They offer advantages over binary outcomes, including increased statistical power and applicability across various illness severities.
- However, understanding and application of ordinal outcomes can be challenging for clinicians and researchers.
Purpose of the Study:
- To provide a practical overview of ordinal outcomes in emergency medicine.
- To discuss the advantages and disadvantages of using ordinal outcomes.
- To describe effect measures and statistical methods for estimating treatment effects with ordinal outcomes.
Main Methods:
- Review of ordinal outcome types, including hierarchical composite endpoints (e.g., Desirability of Outcome Ranking [DOOR]).
- Description of target parameters such as common odds ratio and win ratio.
- Explanation of statistical methods for parameter estimation, including assumptions and limitations.
Main Results:
- Ordinal outcomes provide a flexible, efficient, and nuanced approach to measuring treatment effects.
- Commonly used parameters include the common odds ratio and win ratio.
- Statistical methods for estimation have specific assumptions and limitations that require careful consideration.
Conclusions:
- Ordinal outcomes enhance the measurement of treatment effects in clinical research.
- Effective utilization requires careful planning for estimation and communication of results.
- This review aims to increase accessibility and understanding of ordinal outcomes for clinical researchers.
More Related Videos
14:43A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting
Published on: January 12, 2018
09:52Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide
Published on: January 15, 2017
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Hazard Ratio
For example, in a clinical trial...
Odds Ratio
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Ordinal Level of Measurement
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...