The Price-Bonett approximate Bayes confidence interval for the ratio of probabilities

Described in Chapter 4 "The 2x2 Table"

PriceBonett_approximate_Bayes_CI_2x2(n, a = 1.25, b = 2.5, alpha = 0.05)

Arguments

n: the observed counts (a 2x2 matrix)
a, b: parameters of the beta distribution
alpha: the nominal level, e.g. 0.05 for 95# CIs

Value

An object of the contingencytables_result class, basically a subclass of base::list(). Use the utils::str() function to see the specific elements returned.

Table orientation

In most study designs, rows designate a grouping of the data, for instance, into treatment or exposure groups, while the columns indicate a dichotomous outcome, usually with the first column representing the outcome of interest. This designation of rows and columns may not be relevant in all study designs, please see the introduction to chapter 4 for details.

Examples

# An RCT of high vs standard dose of epinephrine (Perondi et al., 2004)
PriceBonett_approximate_Bayes_CI_2x2(perondi_2004)
#> The Price-Bonett approximate Bayes CI: estimate = 7.0000 (95% CI 0.9205 to 36.5449)

# The association between CHRNA4 genotype and XFS (Ritland et al., 2007)
PriceBonett_approximate_Bayes_CI_2x2(ritland_2007)
#> The Price-Bonett approximate Bayes CI: estimate = 0.0000 (95% CI 0.0014 to 3.4254)