IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v41y2014i11p2539-2556.html
   My bibliography  Save this article

Functional response models for intraclass correlation coefficients

Author

Listed:
  • N. Lu
  • T. Chen
  • P. Wu
  • D. Gunzler
  • H. Zhang
  • H. He
  • X.M. Tu

Abstract

Intraclass correlation coefficients (ICC) are employed in a wide range of behavioral, biomedical, psychosocial, and health care related research for assessing reliability of continuous outcomes. The linear mixed-effects model (LMM) is the most popular approach for inference about the ICC. However, since LMM is a normal distribution-based model and non-normal data are the norm rather than the exception in most studies, its applications to real study data always beg the question of inference validity. In this paper, we propose a distribution-free alternative to provide robust inference based on the functional response models. We illustrate the performance of the new approach using both real and simulated data.

Suggested Citation

  • N. Lu & T. Chen & P. Wu & D. Gunzler & H. Zhang & H. He & X.M. Tu, 2014. "Functional response models for intraclass correlation coefficients," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(11), pages 2539-2556, November.
  • Handle: RePEc:taf:japsta:v:41:y:2014:i:11:p:2539-2556
    DOI: 10.1080/02664763.2014.920780
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2014.920780
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02664763.2014.920780?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. J. Richard Landis & Gary G. Koch, 1975. "A review of statistical methods in the analysis of data arising from observer reliability studies (Part II)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 29(4), pages 151-161, December.
    2. J. Richard Landis & Gary G. Koch, 1975. "A review of statistical methods in the analysis of data arising from observer reliability studies (Part I)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 29(3), pages 101-123, September.
    3. Emily Kistner & Keith Muller, 2004. "Exact distributions of intraclass correlation and Cronbach's alpha with Gaussian data and general covariance," Psychometrika, Springer;The Psychometric Society, vol. 69(3), pages 459-474, September.
    4. Beth Reboussin & Kung-Yee Liang, 1998. "An estimating equations approach for the LISCOMP model," Psychometrika, Springer;The Psychometric Society, vol. 63(2), pages 165-182, June.
    5. Jeanne Kowalski, 2004. "Nonparametric inference for stochastic linear hypotheses: Application to high-dimensional data," Biometrika, Biometrika Trust, vol. 91(2), pages 393-408, June.
    6. H. Zhang & Q. Yu & C. Feng & D. Gunzler & P. Wu & X. M. Tu, 2012. "A new look at the difference between the GEE and the GLMM when modeling longitudinal count responses," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2067-2079, June.
    7. Huiman X. Barnhart & John M. Williamson, 2001. "Modeling Concordance Correlation via GEE to Evaluate Reproducibility," Biometrics, The International Biometric Society, vol. 57(3), pages 931-940, September.
    8. Helena Kraemer, 1981. "Extension of Feldt's approach to testing homogeneity of coefficients of reliability," Psychometrika, Springer;The Psychometric Society, vol. 46(1), pages 41-45, March.
    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. D. Gunzler & W. Tang & N. Lu & P. Wu & X. Tu, 2014. "A Class of Distribution-Free Models for Longitudinal Mediation Analysis," Psychometrika, Springer;The Psychometric Society, vol. 79(4), pages 543-568, October.
    2. Högberg, Hans & Svensson, Elisabeth, 2008. "An Overview of Methods in the Analysis of Dependent ordered catagorical Data: Assumptions and Implications," Working Papers 2008:7, Örebro University, School of Business.
    3. Debby L Gerritsen & Nardi Steverink & Dinnus HM Frijters & Marcel E Ooms & Miel W Ribbe, 2010. "Social well‐being and its measurement in the nursing home, the SWON‐scale," Journal of Clinical Nursing, John Wiley & Sons, vol. 19(9‐10), pages 1243-1251, May.
    4. Christof Schuster & David Smith, 2005. "Dispersion-weighted kappa: An integrative framework for metric and nominal scale agreement coefficients," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 135-146, March.
    5. Fabio Rapallo, 2005. "Algebraic exact inference for rater agreement models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(1), pages 45-66, February.
    6. Cheng, Song-Show & Cheng, Yu-Chun, 1998. "An ordered relation between the ANOVA estimator of the intraclass correlation and a kappa-type statistic in binary data," Statistics & Probability Letters, Elsevier, vol. 38(3), pages 275-280, June.
    7. Högberg, Hans & Svensson, Elisabeth, 2008. "Comparison of methods in the analysis of dependent ordered catagorical data," Working Papers 2008:6, Örebro University, School of Business.
    8. Thiago de Paula Oliveira & John Hinde & Silvio Sandoval Zocchi, 2018. "Longitudinal Concordance Correlation Function Based on Variance Components: An Application in Fruit Color Analysis," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(2), pages 233-254, June.
    9. Sik-Yum Lee & Liang Xu, 2003. "Case-Deletion Diagnostics for Factor Analysis Models With Continuous and Ordinal Categorical Data," Sociological Methods & Research, , vol. 31(3), pages 389-419, February.
    10. Helenowski Irene B & Vonesh Edward F & Demirtas Hakan & Rademaker Alfred W & Ananthanarayanan Vijayalakshmi & Gann Peter H & Jovanovic Borko D, 2011. "Defining Reproducibility Statistics as a Function of the Spatial Covariance Structures in Biomarker Studies," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-21, January.
    11. Xin-Yuan Song & Sik-Yum Lee, 2002. "Analysis of structural equation model with ignorable missing continuous and polytomous data," Psychometrika, Springer;The Psychometric Society, vol. 67(2), pages 261-288, June.
    12. Markus Pannenberg & Martin Spieß, 2007. "GEE Estimation of a Two-Equation Panel Data Model: An Analysis of Wage Dynamics and the Incidence of Profit-Sharing in West Germany," Discussion Papers of DIW Berlin 663, DIW Berlin, German Institute for Economic Research.
    13. Bei Wang & Jeffrey R. Wilson, 2018. "Comparative GMM and GQL logistic regression models on hierarchical data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(3), pages 409-425, February.
    14. Siti Idayu Hasan & Farizah Mohd Hairi & Amer Siddiq Amer Nordin & Mahmoud Danaee, 2019. "Development and Validation of an Evaluation Tool to Measure the Effectiveness of a Smoking Cessation Training among Healthcare Providers in Malaysia: The Providers’ Smoking Cessation Training Evaluati," IJERPH, MDPI, vol. 16(21), pages 1-27, November.
    15. Thomas R. Ten Have & Beth A. Reboussin & Michael E. Miller & Allen Kunselman, 2002. "Mixed Effects Logistic Regression Models for Multiple Longitudinal Binary Functional Limitation Responses with Informative Drop-Out and Confounding by Baseline Outcomes," Biometrics, The International Biometric Society, vol. 58(1), pages 137-144, March.
    16. Ogasawara, Haruhiko, 2023. "The density of the sample correlations under elliptical symmetry with or without the truncated variance-ratio," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    17. Tsai, Miao-Yu, 2015. "Comparison of concordance correlation coefficient via variance components, generalized estimating equations and weighted approaches with model selection," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 47-58.
    18. Chen, Chia-Cheng & Barnhart, Huiman X., 2008. "Comparison of ICC and CCC for assessing agreement for data without and with replications," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 554-564, December.
    19. Tsai, Miao-Yu & Lin, Chao-Chun, 2018. "Concordance correlation coefficients estimated by variance components for longitudinal normal and Poisson data," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 57-70.
    20. Lee, Sik-Yum & Song, Xin-Yuan, 2003. "Maximum likelihood estimation and model comparison of nonlinear structural equation models with continuous and polytomous variables," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 125-142, October.

    More about this item

    Statistics

    Access and download statistics

    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:taf:japsta:v:41:y:2014:i:11:p:2539-2556. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.