Kappa statistic for clustered dichotomous responses from physicians and patients

Chaeryon Kang · Bahjat F. Qaqish · Jane H. Monaco · Stacey Sheridan · Jianwen Cai

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Reliability and Agreement in Measurement Statistical Methods and Bayesian Inference Statistical Methods in Epidemiology

Abstract

The bootstrap method for estimating the standard error of the kappa statistic in the presence of clustered data is evaluated. Such data arise, for example, in assessing agreement between physicians and their patients regarding their understanding of the physician-patient interaction and discussions. We propose a computationally efficient procedure for generating correlated dichotomous responses for physicians and assigned patients for simulation studies. The simulation result demonstrates that the proposed bootstrap method produces better estimate of the standard error and better coverage performance compared with the asymptotic standard error estimate that ignores dependence among patients within physicians with at least a moderately large number of clusters. We present an example of an application to a coronary heart disease prevention study.

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References

1977The Measurement of Observer Agreement for Categorical Data 1960A Coefficient of Agreement for Nominal Scales 1968Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit.1971Measuring nominal scale agreement among many raters.1979Large sample variance of kappa in the case of different sets of raters.1980Extension of the Kappa Coefficient 1996Comparing correlated kappas by resampling: Is one level of agreement significantly different from another?2000Testing the equality of two dependent kappa statistics

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2018Asymptotic variability of (multilevel) multirater kappa coefficients 2017Kappa statistic to measure agreement beyond chance in free-response assessments 2015Kappa statistic for clustered physician–patients polytomous data

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