IDEAS home Printed from
   My bibliography  Save this article

Measurement Equivalence of Ordinal Items: A Comparison of Factor Analytic, Item Response Theory, and Latent Class Approaches


  • Miloš Kankaraš

    () (Tilburg University, Tilburg, The Netherlands)

  • Jeroen K. Vermunt

    (Tilburg University, Tilburg, The Netherlands)

  • Guy Moors

    (Tilburg University, Tilburg, The Netherlands)


Three distinctive methods of assessing measurement equivalence of ordinal items, namely, confirmatory factor analysis, differential item functioning using item response theory, and latent class factor analysis, make different modeling assumptions and adopt different procedures. Simulation data are used to compare the performance of these three approaches in detecting the sources of measurement inequivalence. For this purpose, the authors simulated Likert-type data using two nonlinear models, one with categorical and one with continuous latent variables. Inequivalence was set up in the slope parameters (loadings) as well as in the item intercept parameters in a form resembling agreement and extreme response styles. Results indicate that the item response theory and latent class factor models can relatively accurately detect and locate inequivalence in the intercept and slope parameters both at the scale and the item levels. Confirmatory factor analysis performs well when inequivalence is located in the slope parameters but wrongfully indicates inequivalence in the slope parameters when inequivalence is located in the intercept parameters. Influences of sample size, number of inequivalent items in a scale, and model fit criteria on the performance of the three methods are also analyzed.

Suggested Citation

  • Miloš Kankaraš & Jeroen K. Vermunt & Guy Moors, 2011. "Measurement Equivalence of Ordinal Items: A Comparison of Factor Analytic, Item Response Theory, and Latent Class Approaches," Sociological Methods & Research, , vol. 40(2), pages 279-310, May.
  • Handle: RePEc:sae:somere:v:40:y:2011:i:2:p:279-310

    Download full text from publisher

    File URL:
    Download Restriction: no


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Cernat, Alexandru, 2015. "Using equivalence testing to disentangle selection and measurement in mixed modes surveys," Understanding Society Working Paper Series 2015-01, Understanding Society at the Institute for Social and Economic Research.
    2. Luisa Corrado & Majlinda Joxhe, 2016. "The Effect of Survey Design on Extreme Response Style: Rating Job Satisfaction," CEIS Research Paper 365, Tor Vergata University, CEIS, revised 08 Feb 2016.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:somere:v:40:y:2011:i:2:p:279-310. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (SAGE Publications). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.