Literature DB >> 9192459

Assessing interrater agreement from dependent data.

J M Williamson1, A K Manatunga.   

Abstract

Estimation of interrater agreement for ordered categorical data is examined when the same sample is being assessed by various raters with different methods. We investigate the use of a latent model proposed by Qu, Piedmonte, and Medendorp (1995, Biomerics 51, 268-275) to estimate the correlation between raters for each method, and test for their equality. For each of the assessment methods, these correlations can be interpreted as the variance components of random effects representing subject and rater. This method is applied to an HIV study, in which the amount of ectopy on a woman's cervix is measured by both direct visual assessment and a computer planimetry method.

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Year:  1997        PMID: 9192459

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  6 in total

1.  Measuring intrarater association between correlated ordinal ratings.

Authors:  Kerrie P Nelson; Thomas J Zhou; Don Edwards
Journal:  Biom J       Date:  2020-06-11       Impact factor: 2.207

2.  Assessing the influence of rater and subject characteristics on measures of agreement for ordinal ratings.

Authors:  Kerrie P Nelson; Aya A Mitani; Don Edwards
Journal:  Stat Med       Date:  2017-06-13       Impact factor: 2.373

3.  A SEMI-PARAMETRIC BAYESIAN MODEL OF INTER- AND INTRA-EXAMINER AGREEMENT FOR PERIODONTAL PROBING DEPTH.

Authors:  E G Hill; E H Slate
Journal:  Ann Appl Stat       Date:  2014-03       Impact factor: 2.083

4.  Concordance and consistency of answers to the self-delivered ESPAD questionnaire on use of psychoactive substances.

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Journal:  Int J Methods Psychiatr Res       Date:  2012-02-23       Impact factor: 4.035

5.  Improving the reliability of diagnostic tests in population-based agreement studies.

Authors:  Kerrie P Nelson; Don Edwards
Journal:  Stat Med       Date:  2010-03-15       Impact factor: 2.373

6.  Comparing dependent kappa coefficients obtained on multilevel data.

Authors:  Sophie Vanbelle
Journal:  Biom J       Date:  2017-05-02       Impact factor: 2.207

  6 in total

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