Ordinal Data Scale
- When numbers are purposefully assigned to data that have a sense of rank or order, but the magnitude of difference between those numbers is not known or cannot be measured.
- Ordinal scale data can be in specific order
- Unlike with nominal data, the assigned numbers are not arbitrary
- This type of data scale does not allow for the calculation of an average or mean since the magnitude of difference between each assigned number is not the same.
- Example: An average of the degree of heart failure a group of patients have cannot be described with a mean. A patient cannot have Class 2.5 heart failure, because we do not really know what that means clinically.
- In both of the following examples there is a sense or ranking to condition of the patient. However, the magnitude of difference between each assigned level is not the same.
- New York Heart Association (NYHA) Heart Failure Classification:
- There are 4 classifications (Class I, II, III, & IV)
- There is a sense of order or rank, where a patient with NYHA Class III heart failure has more symptoms and complications than a patient with NYHA Class I heart failure.
- Glasgow Coma Scale:
- Score can range from as low as 3 and as high as 15.
- A trauma patient with a score of 8 is considered more unstable than a trauma patient whose GCS is 14.
- Gaddis ML et al. Introduction to biostatistics: part 1, basic concepts. Ann Emerg Med 1990;19:86-89.
Examples of Ordinal Data