|Title||Kappa statistic for clustered dichotomous responses from physicians and patients.|
|Publication Type||Journal Article|
|Year of Publication||2013|
|Authors||Kang, Chaeryon, Bahjat Qaqish, Jane Monaco, Stacey L. Sheridan, and Jianwen Cai|
|Date Published||2013 Sep 20|
|Keywords||Cluster Analysis, Computer Simulation, Coronary Disease, Humans, Observer Variation, Patient Education as Topic, Patients, Physicians, Statistics as Topic|
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.
|Alternate Journal||Stat Med|
|Original Publication||Kappa statistic for clustered dichotomous responses from physicians and patients.|
|PubMed Central ID||PMC3844626|
|Grant List||K23 HL074375 / HL / NHLBI NIH HHS / United States |
R01 HL057444 / HL / NHLBI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
R01 HL57444 / HL / NHLBI NIH HHS / United States
UL1 RR025747 / RR / NCRR NIH HHS / United States
Kappa statistic for clustered dichotomous responses from physicians and patients.