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Common-method variance

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In applied statistics, (e.g. applied to the social sciences and psychometrics), common-method variance (CMV) is the spurious "variance that is attributable to the measurement method rather than to the constructs the measures represent"[1] or equivalently as "systematic error variance shared among variables measured with and introduced as a function of the same method and/or source"[2]. Studies affected by CMV or common-method bias suffer from false correlations and run the risk of reporting incorrect research results.[1]

Remedies

Ex-ante remedies

Several ex-ante remedies exist that help to avoid or minimize possible common-method variance. Important remedies have been collected by Chang et al. (2010).[3]

Ex-post remedies

Using simulated data sets, Richardson et al. (2009) investigate three ex-post techniques to test for common-method variance: the correlational marker technique, the confirmatory factor analysis (CFA) marker technique, and the unmeasured latent method construct (ULMC) technique. Only the CFA marker technique turns out to provide some value.[2] A comprehensive example of this technique has been demonstrated by Williams et al. (2010).[4]

References

  1. ^ a b Podsakoff, P.M., MacKenzie, S.B., Lee, J.-Y., Podsakoff, N.P., 2003. Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology 88, 879–903.
  2. ^ a b Richardson, H.A., Simmering, M.J., Sturman, M.C., 2009. A tale of three perspectives: Examining post hoc statistical techniques for detection and correction of common method variance. Organizational Research Methods 12, 762–800.
  3. ^ Chang, S.-J., van Witteloostuijn, A., Eden, L., 2010. Common method variance in international business research. J Int Bus Stud 41, 178–184.
  4. ^ Williams, L.J., Hartman, N., Cavazotte, F., 2010. Method variance and marker variables: A review and comprehensive CFA marker technique. Organizational Research Methods 13, 477–514.
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