Abstract
In many paired experiments designed to compare two treatments, various mechanisms can lead to the data being incomplete. Such mechanisms may be of a non-random nature and may depend on the treatment or the outcome. This paper considers several methods for testing the equality of two correlated binomial proportions when the incompleteness is caused by non-random mechanisms. Several simple procedures are justified in certain cases. The tests based on all available data are more efficient compared to those utilizing only portions of the data. McNemar's test based only on the complete paired observations and the likelihood test are the most robust, although no efficient test exists when the mechanisms are not independent.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
