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2. Best readings for SEM 3. OutlineWhat is CMV?Is CMV really exist?How to prevent CMV happen?How to detect CMV?Harman single-factor testCFA Factor testULMC (Unmeasured Latent Method Construct) TechniqueHow to correct CMV?ULMCCorrelational Marker TechniqueCFA Marker TechniqueConclusion 4. What is CMV?Common method variance, may cause systematic measurement error and further bias the estimates of the true relationship among theoretical constructs.Method variance can either inflate or deflate observed relationships between constructs, thus leading to both Type I and Type II errors. 5. What is CMV?The variance of every measured variable can be partitioned into three componentstrait variancemethod variance (one of systematic error),error variance (random error of measurement, nonsystematic influences on measured variables) 6. What is CMV?Total variance= true variance + systematic variance (common method variance)+ random variance (measurement error)method variance is referred to as systematic bias 7. Is CMV really exist?The NO CMV Perspective (Spector, 2006)Noncongeneric Perspective (Lindell & Whitney, 2001)Congeneric Perspective (Williams & Brown, 1994) 8. The NO CMV Perspective (Spector, 2006)CMV Spector CMV1.2. 9. Noncongeneric PerspectiveLindell & Whitney, 2001CMVNoncongeneric PerspectiveCMV CMV1.CMV2. 10. Congeneric PerspectiveWilliams & Brown, 1994CMV 11. How to prevent CMV happen? 12. DeVellis ( 2003) 13. CMV?INFLUENCE?CONTROLEXISTEXISTGAME OVERNOT EXISTNOT EXIST1.Harmans single factor2.CFACMV3.CFA1.ULMC2.CFA MarkerVariable1.ULMC2.CFA Marker as Control VariableCMV 14. How to detect CMV?A priori Marker variablePost Hoc Harmans one factorCFAUnmeasured Latent Method Construct ( ULMC )Correlational Marker TechniqueCFA Marker Technique 15. Selection of Marker VariableA priormarker variable (Ideal marker) marker variable0Post Hoc marker variable (Nonideal marker) 16. Harmans one factorSPSS1() ()1 CMV >50%() 17. Harmans one factor () 18. Harmans one factor () 19. CFACMVLindell & Whitney (2001)1.2.CMV(CMV)3.CMV(Manifest Variables, MVs)4.CMVCMVMVs(w)CMV15.6.CMV 20. CMV CMV CMV0.4 21. ConstructIndicatorSubstantive Factor loadings (R1)R12Method Factor loadings (R2)R22CS1.565.319.205.042CS3.653.426.364.132CS4.712.507.103.011CS5.672.452.178.032SC1.840.706.285.081SC2.817.667.318.101SC3.684.468.072.005SC5.571.326.173.030AL1.754.569.117.014AL2.892.796.285.081AL3.851.724.210.044EI1.866.750.114.013EI2.933.870.175.031EI3.737.543.247.061tangible.912.832-.296.088reliable.749.561.352.124response.722.521.405.164assurence.699.489.414.171empathy.585.342.291.085Average.748.572.211.069 22. CFA1.1 ()2.2CFA3. ?4. CMV5.CMVCMV? 23. CFAModel 1Model 2 24. CFA CMVMODEL2DF2DFPSINGLE FACTOR1477.71521247.1100.000MULTI- FACTOR230.6142 25. CMV?Unmeasured Latent Method Construct ( ULMC )CMV1.CFAModel 12.(CMV) Model 23.CMVModel 34.CMVModel 45.C1~C101 () 56.5 vs.34 () CMV CMV 26. ULMC(William, Cote & Buckley, 1989)Model 1 CFA 27. ULMCModel 2 28. ULMCModel 3CMV 29. ULMCModel 4 30. ULMC5C1~C10 1 () 31. ULMC 32. CFA Marker Technique ApproachWilliams, Hartman, & Cavazotte, (2010).1.Model 1CFA Model2.Model 2Baseline Model3.Model 3Method C Model4.Model 4Method U Model5.Model 5Method R Model 33. Model 1CFA Model Marker Variable CFA 34. Constrain Modelc1=c2=c3=c4=0 Marker W1,W2,W3V1,V2,V3 35. BASELINE MDOELCMV W17 = W18 = W19 = W20 = W21 = W22 = W23 = W24 = W25 = W26 = W27 = W28 = W29 = W30 = W31 = W32=0 constrain model 36. Method C ModelCMV W17=W18= W19=W20= W21=W22= W23=W24= W25=W26= W27=W28= W29=W30= W31=W32 37. Method U ModelCMV 38. Method R ModelC1~C6 CFA C1=.41C2=.57C3=.73C4=.41C5=.48C6=.53 39. Model Comparison TestsModel2dfCFI1.CFA209.061420.9762.Baseline386.161520.9163.Method-C230.421510.9724.Method-U199.571360.9775.Method-R240.431420.965Chi-Square Model Comparison TestsModels2dfp1.Baseline vs. Method C155.741.0002.Method-C vs. Method U30.8415.0053.Method-U vs. Method R40.856.000 40. Model1.CFAMarkerCFA MarkerCMV 1.1ConstrainMarker 0Marker ,2.BaselineMarker 0CFAMarker 3.Method-CMarker CMV 4.Method-UMarker CMV 5.Method-RCFA Method-U/C Marker 41. 1.Baseline vs. Method-CCMV?NoncongenericCMVreject 2.Baseline vs. Method-UCongenericCMVreject 3.Method-C vs. Method-UCMV?Noncongeneric Congeneric reject4.Method-U vs. Method-RCMV?1.Method-UMethod RMethod-U2.RejectMarker 42. How to correct CMV? 43. How to correct CMV?PARTIAL CORRECTIONCONTROL VARIABLE CORRECTION 44. PARTIAL CORRECTION 45. PARTIAL CORRECTION 46. SEM 47. Marker Lindell & Whitney (2001) 48. Marker Lindell & Whitney (2001) 49. No control vs. control 50. EstimateS.E.C.R.PSEM MODEL without CMV