Online Program Home
My Program

Abstract Details

Activity Number: 562
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 11:35 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #321563
Title: Dangers of Misusing Ordinal Data
Author(s): Ivy Liu* and Daniel Fernandez Martinez and Peter Yongqi Gu
Companies: Victoria University of Wellington and New York University and Victoria University of Wellington
Keywords: ordinal data ; Likert scale ; stereotype models ; floor and ceiling effects

In the past 35 years, statisticians have seen substantial methodology developments for ordinal data, yet many researchers in other fields still analyse such data using ordinary normal theory methods by naively assigning scores to ordinal levels. This talk presents a description of the dangers associated with such a naive approach. Along with some well-known disadvantages, such as floor/ceiling effects and the violation of normality assumptions, we show other possible dangers. For example, it is common to believe that when the number of ordered response categories is large, it is acceptable to treat them as continuous. However, it is not necessarily true for survey data. We discuss this issue using an example survey where respondents answered questions using both a 7-point Likert scale and a 0-100 scale. Also, we propose a possible way to evaluate average scores for a group of respondents using stereotype models.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

Copyright © American Statistical Association