Using Coefficient Alpha in Large-Scale Surveys With Likert Scales and Non-Normal Distributions (Poster 28)

• In Event: AERA Poster Session Three
  In Poster Session: Measurement Theory and Application 2

Abstract

We compared alpha and recently proposed potential competitors (ordinal alpha, omega total, omega RT, omega h, GLB, and coefficient H) when they were used with non-normal continuous and discrete data. Results showed that for continuous data, estimation bias was large only when non-normality was severe, and non-normality was a problem with weak items. For Likert scales, other than omega h, most indices were acceptable with non-normal data, and four or more scale points were better. For exponentially distributed data, omega RT was quite robust for all distributions, and bias was generally larger for the binomial-beta distribution. An examination with large-scale surveys suggested that non-normality was not a critical issue as most of the actual items were at worst moderately non-normal.

Authors

• Leifeng Xiao, Chinese University of Hong Kong
  Presenting Author

• Luyang Guo, Chinese University of Hong Kong
  Presenting Author

• Dan Wang, The Chinese University of Hong Kong
  Presenting Author

• Kit-Tai Hau, Chinese University of Hong Kong
  Presenting Author