Common Method Bias using Harman's Single Factor Test in SPSS AMOS

Harman Single Factor Test


This tutorials discusses the Common Method Bias using Harman’s Single Factor Test

Common Method Bias

  • Over the last 10 years, more and more attention has been paid to the idea of common method bias (CMB) in the measurement analysis phase.
  • Common method bias is the inflation (or in rare cases deflation) of the true correlation among observable variables in a study.
  • Research has shown that because respondents are replying to survey questions about independent and dependent variables at the same time, this can artificially inflate the covariation (which leads to biased parameter estimates). In this video we are going to discuss how to assess and control for common method bias.
  • The methods include
    • –Harman’s Single Factor Test
    • –Latent Common Method Factor

Harman's Single Factor Test

  • This simplistic test performs an EFA with all the indicators in your model to determine if one single factor will emerge.
  • If a single factor does appear, then common method bias is said to be present in the data.
  • You will also see a Harman’s single factor test performed with a CFA where all indicators are purposely loaded on one factor to determine model fit.
  • If you have an acceptable model fit with the one construct model, then you have a method bias.
  • There is an ongoing debate as to whether Harman’s single factor test is an appropriate test to determine common method bias. On one side, researchers have questioned this approach and have concluded that it is insufficient to determine if common method bias is present (Malhotra et al. 2007; Chang et al. 2010).
  • Other researchers (Fuller et al. 2016) have argued that if common method bias is strong enough to actually bias results, then Harman’s single factor test is sensitive enough to determine if a problem exists.
  • While Harman’s single factor test is easy to implement, it is a relatively insensitive test to determine common method bias compared to other post-hoc tests.
  • In Conclusion, If you know a test is inferior to others, then there is very little justification for using this method.


  • Collier, J. E. (2020). Applied structural equation modeling using AMOS: Basic to advanced techniques. Routledge.
  • Chang, Sea-Jin, Arjen van Witteloostuijn, and Lourraine Eden. (2010), “From the Editors: Common Method Variance
    in International Business Research”, Journal of International Business Studies, 41 (2), 178–184.
  • Fuller, Christie M., Marcia J. Simmering, Guclu Atinc, Yasemin Atinc, and Barry J. Babin. (2016), “Common Methods
    Variance Detection in Business Research”, Journal of Business Research, 69 (8), 3192–3198.
  • Malhotra, Naresh K., Ashutosh Patil, and Sung S. Kim. (2007), “Bias Breakdown”, Marketing Research, 19 (1), 24–29.

Video Tutorial