Related Experiment Video
Updated: May 9, 2025

Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
Published on: October 11, 2018
On the efficacy of psychological separation to address common method variance: Experimental evidence and a guiding
Alex L Rubenstein1, Lauren S Simon2, John D Kammeyer-Mueller3
1Department of Management, College of Business, University of Central Florida.
Abstract:
Common method variance (CMV) substantially impacts how scholars conduct and review research. Several procedural and statistical remedies have been proposed to address the potential biasing effects that can result from CMV in data procured from a single source on a single occasion. Among them, temporal separation and distinct source designs have been the most popular. Psychological separation (PS) has also been proposed as a way to address CMV, by diverting respondents' attention from previously accessed memories, disrupting response consistency patterns, and improving effortful responding. The present research attempted to create efficacious PS through a cognitive interference task administered midway through a survey, thereby attenuating correlations that could be affected by CMV to varying degrees. In an initial study and a constructive replication, our results show that a PS intervention of at least 7.5-min attenuated several relationships to levels significantly lower than those in a single source on a single occasion design, but to an extent consistent with the attenuation achieved by temporal separation or distinct source designs. These findings suggest that under appropriate circumstances, PS is an effective strategy to address certain forms of CMV. We conclude by providing a decision guide for responsibly choosing a research design in light of various theoretical, methodological, and logistical considerations, as well as offering several additional PS task examples that can be deployed in future studies. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Related Concept Videos
Statistical Significance
Empirical Method to Interpret Standard Deviation
This rule is used widely in statistics to calculate the proportion of data values...
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Behrens–Fisher Test
This test...
Data Validation
Key parameters for method validation include:

