Four Research Designs and a Comprehensive Analysis Strategy for Investigating Common Method Variance with Self-Report Measures Using Latent Variables

• Published in: Journal of business and psychology Vol. 31; no. 3; pp. 339 - 359
• Main Authors: Williams, Larry J., McGonagle, Alyssa K.
• Format: Journal Article
• Language: English
• Published: New York Springer Science + Business Media 01-09-2016; Springer US; Springer Nature B.V
• Subjects: Behavioral psychology; Behavioral Science and Psychology; Bias; Business and Management; Community and Environmental Psychology; Design; Industrial and Organizational Psychology; ORIGINAL PAPER; Personality and Social Psychology; Psychology; Social Sciences; Statistical methods; Studies; Variables; Variance analysis; Common method variance; Measured method variable; Measured Cause Variable; Hybrid Method Variables Model; Unmeasured latent method factor; Marker Variable
• ISSN: 0889-3268; 1573-353X
• DOI: 10.1007/s10869-015-9422-9

Common method variance (CMV) is an ongoing topic of debate and concern in the organizational literature. We present four latent variable confirmatory factor analysis model designs for assessing and controlling for CMV—those for unmeasured latent method constructs, Marker Variables, Measured Cause Variables, as well as a new hybrid design wherein these three types of method latent variables are used concurrently. We then describe a comprehensive analysis strategy that can be used with these four designs and provide a demonstration using the new design, the Hybrid Method Variables Model. In our discussion, we comment on different issues related to implementing these designs and analyses, provide supporting practical guidance, and, finally, advocate for the use of the Hybrid Method Variables Model. Through these means, we hope to promote a more comprehensive and consistent approach to the assessment of CMV in the organizational literature and more extensive use of hybrid models that include multiple types of latent method variables to assess CMV.