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  • Intraclass correlation coefficient

    Hello,
    I am struggling with ICC for 3 days.
    Can anyone help me?
    I am doing this research for my ophthalmology department.
    Just to put you in context, measuring choroidal thickness has become an important tool for assessing its function and pathophysiology in many chorioretinal disorders.
    However, there’s only one way to do it: manually. We have to find the upper and lower limits of the choroidal layer in a optical coherence tomography of the retina and measuring with a “rule” (a caliper built in the optical device)
    Naturally, ophthalmologists think that this may be a subjective measurement, leading to variation between occasions in the same operator or with different operators.

    We have made this study in my department: 2 different operators (an ophthalmologist and a resident in ophthalmology ) have measured the subfoveal choroidal thickness of nearly 80 eyes of 40 patients in two different occasions (with one month of interval). Of course the three of us were blinded for our own previous measurements and each other’s measurements.

    I have to make the statistical analysis of the intraobserver variability and inter observer variability.

    I am writing because I am confused about the statistical test I should use.

    Many studies used intraclass correlation coefficient (CCC) and Bland-Altman plots. How can I do this using STATA? What model should I use?
    one way, two way random effects or two way mixed model?
    I read this in a blogue: to calculate an ICC in Stata Version 12.1 you will need your data in long format (ie. One column for the variable of interest, one column indicating which survey participant each row pertains to, and one column indicating which interviewer each row pertains to). Keep in mind that each survey participant is seen by a number of interviewers. The Intra-Class Correlation Coefficient is then calculated using Stata’s “icc” command.
    I don't understand how I should change my columns...
    Thank you all.




  • #2
    Ines,

    The ICC is indeed an appropriate method for this sort of problem. Please indicate how your data are currently stored so we can advise as to how to reformat them (if necessary) for the icc command.

    As to which kind of model to use, the Stata manual for icc has a good discussion of this issue: http://www.stata.com/manuals13/ricc.pdf. Here is brief summary:
    • One-way random effects: each measurement done by a random set of evaluators
    • Two-way random effects: each measurement done by the same set of evaluators, randomly chosen from all possible evaluators.
    • Two-way mixed effects: each measurement done by the same set of evaluators, who are the only possible evaluators.
    It sounds like the first is not what you want; the choice between random and mixed requires more information about your study design and how you plan to use the results.

    Regards,
    Joe

    Comment


    • #3
      Hi Ines and Joe,
      I have pretty much the same problem: I would like to calculate my ICCs but I am not entirely sure what method I should use.
      Can you please help me? Shall I send my study design etc.?

      Thank you very much for your time and help,

      Best wishes,

      Leo

      Comment


      • #4
        Hello, Ines and Leonardo,

        As a suggestion, you could type "help icc" and, above to the left, click on [R] icc.

        It's from Stata Base Reference Manual.

        There is an interesting explanation, and, just to let you know how they approach the problem, I pasted a few lines:

        "1. Is a one-way or two-way analysis-of-variance model appropriate for your study?
        2. Are differences between raters’ mean ratings relevant to the reliability of interest?
        3. Is the unit of analysis an individual rating or the mean rating over several raters?
        4. Is the consistency of agreement or the absolute agreement of ratings of interest?"

        I believe these answers are exactly what you're searching for.

        Best,

        Marcos
        Best regards,

        Marcos

        Comment


        • #5
          Originally posted by Joe Canner View Post
          Ines,

          The ICC is indeed an appropriate method for this sort of problem. Please indicate how your data are currently stored so we can advise as to how to reformat them (if necessary) for the icc command.

          As to which kind of model to use, the Stata manual for icc has a good discussion of this issue: http://www.stata.com/manuals13/ricc.pdf. Here is brief summary:
          • One-way random effects: each measurement done by a random set of evaluators
          • Two-way random effects: each measurement done by the same set of evaluators, randomly chosen from all possible evaluators.
          • Two-way mixed effects: each measurement done by the same set of evaluators, who are the only possible evaluators.
          It sounds like the first is not what you want; the choice between random and mixed requires more information about your study design and how you plan to use the results.

          Regards,
          Joe

          Is there any way ICC can be done in Stata version 12?

          Comment


          • #6
            Hi all,
            I found some error in the http://www.stata.com/manuals13/ricc.pdf
            BMS should multiple K, JMS should multiple N.

            Hope this message helps.

            Regards,
            Feng Susan

            Comment

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