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An Exact Test for Detecting Inconsistency in Readers Interpretation Over Time in Screening Mammograms
Author(s) -
Lee JiHyun,
Eschrich Steven,
Beam Craig
Publication year - 2007
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.200610314
Subject(s) - overdispersion , binomial distribution , statistics , interpretation (philosophy) , mathematics , population , statistical hypothesis testing , binomial (polynomial) , computer science , negative binomial distribution , medicine , poisson distribution , environmental health , programming language
Radiologists' interpretation on screening mammograms is measured by accuracy indices such as sensitivity and specificity. The hypothesis that radiologists' interpretation on screening mammograms is constant across time can be tested by measuring overdispersion. However, small sample sizes are problematic for the accuracy of asymptotic approaches. In this article, we propose an exact conditional distribution for testing overdispersion of the binomial assumption that is assumed for the accuracy indices. An exact p ‐value can be defined from the developed distribution. We also describe an algorithm for computing this exact test. This proposed method is applied to data from a study in reading screening mammograms in a population of US radiologists (Beam et al., 2003). The exact method is compared analytically with a currently available method based on large sample approximations. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)