On the Folly of Introducing A (Time-Based UMV), While Designing for B (Time-Based CMV)
Document Type
Article
Publication Date
3-15-2023
Department 1
Management
Abstract
To mitigate concerns of common method variance (CMV), researchers often separate predictor and criterion variables, with temporal separation being the most widely applicable option (e.g., Podsakoff et al., 2012). However, temporal separation is empirically understudied relative to other CMV corrections (Lance et al., 2009; Podsakoff et al., 2012). And despite being recommended, CMV corrections may actually underestimate true correlations by as much as 50% (e.g., Lance et al., 2010; Spector, 2006). In fact, uncommon method variance (UMV) theory (Spector et al., 2019) suggests that temporal separation attenuates observed correlations by way of unshared sources of method variance—such as “Time 1” and “Time 2” data collections (Spector et al., 2019). [excerpt]
DOI
10.1177/01466216231165304
Recommended Citation
Brawley Newlin, A. (2023). On the Folly of Introducing A (Time-Based UMV), While Designing for B (Time-Based CMV). Applied Psychological Measurement, 47(3), 253-256. https://doi.org/10.1177/01466216231165304
Required Publisher's Statement
This article is available from the publisher's website.