title: Shame for disrespecting evidence: the personal consequences of insufficient respect for structural equation model testing.
abstract: BACKGROUND
  Inappropriate and unacceptable disregard for structural equation model (SEM) testing can be traced back to: factor-analytic inattention to model testing, misapplication of the Wilkinson task force's [Am Psychol 54:594-604, 1999] critique of tests, exaggeration of test biases, and uncomfortably-numerous model failures.
  
  
  CONCLUSIONS
  The arguments for disregarding structural equation model testing are reviewed and found to be misguided or flawed. The fundamental test-supporting observations are: a) that the null hypothesis of the χ2 structural equation model test is not nil, but notable because it contains substantive theory claims and consequences; and b) that the amount of covariance ill fit cannot be trusted to report the seriousness of model misspecifications. All covariance-based fit indices risk failing to expose model problems because the extent of model misspecification does not reliably correspond to the magnitude of covariance ill fit - seriously causally misspecified models can fit, or almost fit.
  
  
  CONCLUSIONS
  The only reasonable research response to evidence of non-chance structural equation model failure is to diagnostically investigate the reasons for failure. Unfortunately, many SEM-based theories and measurement scales will require reassessment if we are to clear the backlogged consequences of previous deficient model testing. Fortunately, it will be easier for researchers to respect evidence pointing toward required reassessments, than to suffer manuscript rejection and shame for disrespecting evidence potentially signaling serious model misspecifications.
authors.affiliation: Department of Sociology, University of Alberta, Edmonton, Canada. LHayduk@ualberta.ca.
authors.forename: Leslie A
authors.initials: LA
authors.lastname: Hayduk
mesh_terms: D000704:Analysis of Variance; D016009:Chi-Square Distribution; D006801:Humans; D015233:Models, Statistical; D011594:Psychometrics; D012107:Research Design; D012752:Shame