Will the Real Correlation Please Stand Up? An Examination of the Effectiveness of Statistical Corrections for Common Method Variance Using Data Simulation

Richardson, Hettie A.; Simmering, Marcia J.; Sturman, Michael C.

dc.contributor.author	Richardson, Hettie A.
dc.contributor.author	Simmering, Marcia J.
dc.contributor.author	Sturman, Michael C.
dc.date.accessioned	2020-09-11T01:57:42Z
dc.date.available	2020-09-11T01:57:42Z
dc.date.issued	2004-01-01
dc.identifier.other	4758111
dc.identifier.uri	https://hdl.handle.net/1813/71320
dc.description.abstract	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.
dc.language.iso	en_US
dc.rights	Required Publisher Statement: ©Southern Management Association. Reprinted with permission. All rights reserved.
dc.subject	CMV
dc.subject	common method variance
dc.subject	statistical techniques
dc.subject	post hoc
dc.subject	corrections
dc.subject	data simulation
dc.title	Will the Real Correlation Please Stand Up? An Examination of the Effectiveness of Statistical Corrections for Common Method Variance Using Data Simulation
dc.type	conference papers and proceedings
dc.description.legacydownloads	Sturman97_Will_the_real_correlation_please_stand_up.pdf: 371 downloads, before Aug. 1, 2020.
local.authorAffiliation	Richardson, Hettie A.: Louisiana State University
local.authorAffiliation	Simmering, Marcia J.: Louisiana State University
local.authorAffiliation	Sturman, Michael C.: mcs5@cornell.edu Cornell University