The Blaker mid-P confidence interval for the binomial probability

Source: R/Blaker_midP_CI_1x2.R

The Blaker mid-P confidence interval for the binomial probability Described in Chapter 2 "The 1x2 Table and the Binomial Distribution"

Blaker_midP_CI_1x2(X, n, alpha = 0.05)

Arguments

X

the number of successes

n

the total number of observations

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.

References

Blaker H (2000) Confidence curves and improved exact confidence intervals for discrete distributions. The Canadian Journal of Statistics; 28:783-798

Examples

Blaker_midP_CI_1x2(singh_2010["1st", "X"], singh_2010["1st", "n"])
#> The Blaker mid-P CI: estimate = 0.4690 (95% CI 0.4267 to 0.5113)
Blaker_midP_CI_1x2(singh_2010["2nd", "X"], singh_2010["2nd", "n"])
#> The Blaker mid-P CI: estimate = 0.4951 (95% CI 0.4465 to 0.5438)
Blaker_midP_CI_1x2(singh_2010["3rd", "X"], singh_2010["3rd", "n"])
#> The Blaker mid-P CI: estimate = 0.6168 (95% CI 0.5421 to 0.6866)
with(singh_2010["4th", ], Blaker_midP_CI_1x2(X, n)) # alternative syntax
#> The Blaker mid-P CI: estimate = 0.7333 (95% CI 0.5905 to 0.8426)
Blaker_midP_CI_1x2(ligarden_2010["X"], ligarden_2010["n"])
#> The Blaker mid-P CI: estimate = 0.8125 (95% CI 0.5656 to 0.9347)