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Review of alternative approaches to calculation of a confidence interval for the odds ratio of a 2 × 2 contingency table
Author(s) -
Ruxton Graeme D.,
Neuhäuser Markus
Publication year - 2013
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/j.2041-210x.2012.00250.x
Subject(s) - contingency table , confidence interval , categorical variable , statistics , odds ratio , null hypothesis , mathematics , table (database) , statistic , type i and type ii errors , test statistic , exact test , interval (graph theory) , statistical hypothesis testing , computer science , econometrics , data mining , combinatorics
SummaryA common situation in biology is where we have count data and wish to explore whether there is an association between two categorical variables, each with two levels (a 2 × 2 contingency table). The size of the association can be measured using the odds ratio, with a confidence interval for this measure enclosing unity suggesting no evidence of an association. However, there is no universally agreed method for calculating such a confidence interval. Here, we provide a review of some commonly used and recently suggested methods. Of all of the methods currently available, the unconditional approach based on the score statistic was consistently closest to the nominal type I error level in our investigations, and this is the method we generally recommend. This method also offers good agreement with P ‐values from null hypothesis testing using the method of Fisher‐Boschloo. However, some scientists may prefer the recently developed minlike or B laker methods, which offered better agreement with P ‐values calculated using F isher's E xact test or B laker's E xact test, respectively. Lastly, where calculation without use of a computer is required, we recommend the W oolf method with H aldane‐ A nscombe correction.