A concern of researchers is the risk of measurement error due to common method variance (CMV) when using self-reported data. The present study addresses this concern by empirically comparing four techniques for correcting CMV. Eighteen simulated datasets, with varying degrees of method variance, group agreement, and reliability, were analyzed. Based on these analyses, benefits and drawbacks of correcting CMV using the different techniques are detailed. Recommendations for using the different techniques are also provided.