IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v55y2011i7p2354-2362.html
   My bibliography  Save this article

Generalized estimating equations with model selection for comparing dependent categorical agreement data

Author

Listed:
  • Tsai, Miao-Yu
  • Wang, Jung-Feng
  • Wu, Jia-Ling

Abstract

Many studies in biomedical fields are carried out using diagnoses reported by different raters to evaluate the agreement of multiple ratings. The most popular indices of agreement are kappa measures including Cohen's kappa and weighted kappa for binary and ordinal outcomes, respectively. However, when raters assess the same observation on two or more occasions, these ratings are dependent and so the correlation between kappa estimates must be considered when making inferences. In this paper, we focus on testing the equality of correlated kappa coefficients using the generalized estimating equation (GEE) approach and applying quasi-likelihood under the independence model criterion (QIC) measures for model selection. Simulation studies are conducted to compare the performance between GEE with and without QIC measures, weighted least squares (WLS) and independence approaches for binary and ordinal data. Two applications are illustrated: a comparison of two methods for assessing cervical ectopy, and similarity in myopic status for monozygous twins and dizygous twins. We conclude that when performing the QIC model-selection procedure in GEE models and taking into account the correlation between kappa measures, it leads to nominal type I errors and larger powers.

Suggested Citation

  • Tsai, Miao-Yu & Wang, Jung-Feng & Wu, Jia-Ling, 2011. "Generalized estimating equations with model selection for comparing dependent categorical agreement data," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2354-2362, July.
  • Handle: RePEc:eee:csdana:v:55:y:2011:i:7:p:2354-2362
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(11)00047-8
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huiman X. Barnhart & John M. Williamson, 2002. "Weighted Least-Squares Approach for Comparing Correlated Kappa," Biometrics, The International Biometric Society, vol. 58(4), pages 1012-1019, December.
    2. R. Gonin & S. R. Lipsitz & G. M. Fitzmaurice & G. Molenberghs, 2000. "Regression modelling of weighted κ by using generalized estimating equations," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(1), pages 1-18.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hung‐Mo Lin & John M. Williamson & Stuart R. Lipsitz, 2003. "Calculating power for the comparison of dependent κ‐coefficients," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(4), pages 391-404, October.
    2. Huiman X. Barnhart & John M. Williamson, 2002. "Weighted Least-Squares Approach for Comparing Correlated Kappa," Biometrics, The International Biometric Society, vol. 58(4), pages 1012-1019, December.
    3. Yang, Zhao & Zhou, Ming, 2015. "Weighted kappa statistic for clustered matched-pair ordinal data," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 1-18.

    Corrections

    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:eee:csdana:v:55:y:2011:i:7:p:2354-2362. See general information about how to correct material in RePEc.

    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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.