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Exact interval estimators for some commonly used measures of binary agreement
Author(s) -
Lui KungJong
Publication year - 2019
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.8441
Subject(s) - estimator , binary number , interval (graph theory) , monte carlo method , measure (data warehouse) , statistics , binary data , interval estimation , computer science , confidence interval , homogeneous , interval data , mathematics , statistical physics , data mining , physics , arithmetic , combinatorics
We develop exact interval estimators for some commonly used classical measures of agreement in binary responses. We apply Monte Carlo simulation to evaluate the performance of these estimators. When the measure of agreement is homogeneous, we note that extending the results presented here to accommodate stratified analysis is straightforward. We use the data taken from a survey studying the agreement of religious identifications and the data taken from a study assessing the diagnostic performance of Whooley questions for major depression disorder to illustrate the use of these interval estimators.