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

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dc.contributor.authorRichardson, Hettie A.
dc.contributor.authorSimmering, Marcia J.
dc.contributor.authorSturman, Michael C.
dc.date.accessioned2020-09-11T01:57:42Z
dc.date.available2020-09-11T01:57:42Z
dc.date.issued2004-01-01
dc.description.abstractA 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.description.legacydownloadsSturman97_Will_the_real_correlation_please_stand_up.pdf: 371 downloads, before Aug. 1, 2020.
dc.identifier.other4758111
dc.identifier.urihttps://hdl.handle.net/1813/71320
dc.language.isoen_US
dc.rightsRequired Publisher Statement: ©Southern Management Association. Reprinted with permission. All rights reserved.
dc.subjectCMV
dc.subjectcommon method variance
dc.subjectstatistical techniques
dc.subjectpost hoc
dc.subjectcorrections
dc.subjectdata simulation
dc.titleWill the Real Correlation Please Stand Up? An Examination of the Effectiveness of Statistical Corrections for Common Method Variance Using Data Simulation
dc.typeconference papers and proceedings
local.authorAffiliationRichardson, Hettie A.: Louisiana State University
local.authorAffiliationSimmering, Marcia J.: Louisiana State University
local.authorAffiliationSturman, Michael C.: mcs5@cornell.edu Cornell University

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