What question did this study set out to answer?

To present a statistical model that uses partial correlation analysis to control for common method variance in cross-sectional attitude-behavior research.

January 1, 2001Journal of Applied Psychology

Accounting for common method variance in cross-sectional research designs.

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To present a statistical model that uses partial correlation analysis to control for common method variance in cross-sectional attitude-behavior research.
Formulated a mathematical model applying partial correlation analysis to adjust observed bivariate correlations for common method variance (CMV) contamination.
Outlined specific questionnaire design techniques intended to enhance the statistical precision of the CMV adjustment procedure.
The adjustment procedure enables researchers to determine whether the statistical and practical significance of a predictor is driven by method bias rather than a true relationship.
Identified survey construction strategies that systematically improve the precision of post-hoc partial correlation adjustments for CMV.

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Implication

Methodological study demonstrates a partial correlation approach to adjust for common method variance in cross-sectional surveys, highlighting ways to prevent false significance in predictor models.

Cite This Study

Lindell et al. (2001) studied this question.

synapsesocial.com/papers/69d75790ef4aa71f97f30ce2 https://doi.org/10.1037/0021-9010.86.1.114

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Implication

Methodological study demonstrates a partial correlation approach to adjust for common method variance in cross-sectional surveys, highlighting ways to prevent false significance in predictor models.

Accounting for common method variance in cross-sectional research designs.

Key Points

Discussion

Implication

Cite This Study

Accounting for common method variance in cross-sectional research designs.

Key Points

Discussion

Implication

Cite This Study

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