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      Measurement Invariance Conventions and Reporting: The State of the Art and Future Directions for Psychological Research

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          Abstract

          Measurement invariance assesses the psychometric equivalence of a construct across groups or across time. Measurement noninvariance suggests that a construct has a different structure or meaning to different groups or on different measurement occasions in the same group, and so the construct cannot be meaningfully tested or construed across groups or across time. Hence, prior to testing mean differences across groups or measurement occasions (e.g., boys and girls, pretest and posttest), or differential relations of the construct across groups, it is essential to assess the invariance of the construct. Conventions and reporting on measurement invariance are still in flux, and researchers are often left with limited understanding and inconsistent advice. Measurement invariance is tested and established in different steps. This report surveys the state of measurement invariance testing and reporting, and details the results of a literature review of studies that tested invariance. Most tests of measurement invariance include configural, metric, and scalar steps; a residual invariance step is reported for fewer tests. Alternative fit indices (AFIs) are reported as model fit criteria for the vast majority of tests; χ 2 is reported as the single index in a minority of invariance tests. Reporting AFIs is associated with higher levels of achieved invariance. Partial invariance is reported for about one-third of tests. In general, sample size, number of groups compared, and model size are unrelated to the level of invariance achieved. Implications for the future of measurement invariance testing, reporting, and best practices are discussed.

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          Author and article information

          Journal
          8214761
          20470
          Dev Rev
          Dev Rev
          Developmental review : DR
          0273-2297
          25 June 2016
          29 June 2016
          September 2016
          01 September 2017
          : 41
          : 71-90
          Affiliations
          Eunice Kennedy Shriver National Institute of Child Health and Human Development
          Author notes
          Address Correspondence to: Diane L. Putnick, Eunice Kennedy Shriver National Institute of Child Health and Human Development, 6705 Rockledge Drive, Suite 8030, Bethesda, MD 20892, 301-496-6291, putnickd@ 123456mail.nih.gov
          Article
          PMC5145197 PMC5145197 5145197 nihpa797990
          10.1016/j.dr.2016.06.004
          5145197
          27942093
          5fd60756-4861-4ee0-93e7-fd75b22ca445
          History
          Categories
          Article

          multiple-group analysis,confirmatory factor analysis,structural equation modeling,measurement invariance,Comparative psychology

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