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  • Marker variables provide an efficacious means of post hoc detection of common method variance (CMV) in data. These variables are measured in the same way as substantive variables, but because they are conceptually unrelated to the variables of interest, they are believed to be a proxy for CMV. Although marker variables have demonstrated effectiveness, questions remain as to what they actually measure, and thus, why they work. This lack of knowledge prevents researchers from choosing appropriate marker variables to include in same source surveys. The purpose of this research is to determine how four different marker variables account for common rater effects which can cause CMV. A metacognitive approach is used to develop an empirical study using two samples, with a focus on the specific rater effects of mood state, transient mood, consistency motif, and illusory correlations. Findings indicate that these marker variables elicit similar respondent reactions and do not create a notable psychological separation between substantive variables. Additionally, there is evidence that respondents’ use of consistency motifs and illusory correlations influence substantive variable relations. Finally, using the confirmatory factor analysis marker technique, data from two samples indicate the presence of CMV, but not bias from CMV, indicating that the problem of artificially inflated results due to CMV may be overstated.

  • Social and behavioral science researchers who use survey data are vigilant about data quality, with an increasing emphasis on avoiding common method variance (CMV) and insufficient effort responding (IER). Each of these errors can inflate and deflate substantive relationships, and there are both a priori and post hoc means to address them. Yet, little research has investigated how both IER and CMV are affected with the use of these different procedural or statistical techniques used to address them. More specifically, if interventions to reduce IER are used, does this affect CMV in data? In an experiment conducted both in and out of the laboratory, we investigate the impact of attentiveness interventions, such as a Factual Manipulation Check (FMC) on both IER and CMV in same-source survey data. In addition to typical IER measures, we also track whether respondents play the instructional video and their mouse movement. The results show that while interventions have some impact on the level of participant attentiveness, these interventions do not appear to lead to differing levels of CMV.

Last update from database: 3/13/26, 4:15 PM (UTC)

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