title: Strengthening the assessment of factorial invariance across population subgroups: a commentary on Varni et al. (2013).
abstract: OBJECTIVE
  This article provides a commentary in response to "Varni et al. (Qual Life Res. doi: 10.1007/s11136-013-0370-4 , 2013)."
  
  
  RESULTS
  The commentary argues that the approximate model fit indexes commonly used in maximum-likelihood confirmatory factor analysis and factorial invariance testing are seriously flawed, as they overlook potentially serious model misspecifications that could bias parameter estimates and compromise inference.
  
  
  CONCLUSIONS
  Flexible and convenient Bayesian estimation approaches are presented that can substantially aid in: (1) resolving commonly encountered specification errors in confirmatory factor models and (2) locating specific measurement parameters that are non-invariant across population subgroups. It is recommended that these methods should be more widely adopted for evaluating the factorial invariance of patient-reported outcome measures and other types of instruments.
authors.affiliation: National Crime Prevention Centre, Public Safety Canada, 269 Laurier Avenue West, Ottawa, ON, K1A 0P8, Canada, cameron.mcintosh@ps-sp.gc.ca.
authors.forename: Cameron N
authors.initials: CN
authors.lastname: McIntosh
mesh_terms: D005221:Fatigue / Q000503:physiopathology*; D005260:Female; D006801:Humans; D008297:Male; D011594:Psychometrics / Q000295:instrumentation*; D011788:Quality of Life