Skip to main content
Article
Unconditional efficient one-sided confidence limits for the odds ratio based on conditional likelihood
Statistics in Medicine (2007)
  • Chris Lloyd
  • Max Moldovan
Abstract

We compare various one-sided confidence limits for the odds ratio in a 2x2 table. The first group of limits relies on first order asymptotic approximations and includes limits based on the (signed) likelihood ratio, score and Wald statistics. The second group of limits is based on the conditional tilted hypergeometric distribution, with and without mid-P correction. All these limits have poor unconditional coverage properties and so we apply the general transformation of Buehler (1957) to obtain limits which are unconditionally exact. The performance of these competing exact limits is assessed across a range of sample sizes and parameter values by looking at their mean size. The results indicate that Buehler limits generated from the conditional likelihood have the best performance, with a slight preference for the mid-P version. This confidence limit has not been proposed before and is recommended for general use, especially when the underlying probabilities are not extreme.

Keywords
  • nuisance parameters,
  • exact limit,
  • Berger-Boos,
  • conditional inference
Publication Date
Summer 2007
Citation Information
Chris Lloyd and Max Moldovan. "Unconditional efficient one-sided confidence limits for the odds ratio based on conditional likelihood" Statistics in Medicine Vol. 26 (2007)
Available at: http://works.bepress.com/chris_lloyd/5/