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MAXIMUM LIKELIHOOD ESTIMATION OF THE KAPPA COEFFICIENT FROM BIVARIATE LOGISTIC REGRESSION
Author(s) -
SHOUKRI M. M.,
MIAN I. U. H.
Publication year - 1996
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/(sici)1097-0258(19960715)15:13<1409::aid-sim269>3.0.co;2-n
Subject(s) - statistics , mathematics , kappa , logit , bivariate analysis , estimator , logistic regression , covariate , econometrics , cohen's kappa , null hypothesis , sample size determination , restricted maximum likelihood , monte carlo method , linear regression , maximum likelihood , geometry
We propose a maximum likelihood estimator (MLE) of the kappa coefficient from a 2×2 table when the binary ratings depend on patient and/or clinician effects. We achieve this by expressing the logit of the probability of positive rating as a linear function of the subject‐specific and the rater‐specific covariates. We investigate the bias and variance of the MLE in small and moderate size samples through Monte Carlo simulation and we provide the sample size calculation to detect departure from the null hypothesis H 0 : kappa = κ 0 in the direction of H 1 : kappa>κ 0 .