| EHypMidP {CooccurrenceAffinity} | R Documentation |
Quantile of the Extended Hypergeometric distribution approximated by the midP distribution function
Description
This function does the analogous calculation to that of EHypQuInt, but with the Extended Hypergeometric distribution function F(x) = F(x,mA,mB,N, exp(alpha)) replaced by (F(x) + F(x-1))/2.
Usage
EHypMidP(x, marg, lev)
Arguments
x |
integer co-occurrence count that should properly fall within the closed interval [max(0,mA+mB-N), min(mA,mB)] |
marg |
a 3-entry integer vector (mA,mB,N) consisting of the first row and column totals and the table total for a 2x2 contingency table |
lev |
a confidence level, generally somewhere from 0.8 to 0.95 (default 0.95) |
Details
This function does the analogous calculation to that of CI.CP, but with the Extended Hypergeometric distribution function F(z, alpha) = F(z,mA,mB,N, exp(alpha)) replaced by (F(z,alpha) + F(z-1,alpha))/2.
Value
This function returns the interval of alpha values with endpoints (F(x,alpha)+F(x-1,alpha))/2 = (1+lev)/2 and (F(x,alpha)+F(x+1,alpha))/2 = (1-lev)/2.
The idea of calculating a Confidence Interval this way is analogous to the midP CI used for unknown binomial proportions (Agresti 2013, p.605).
Author(s)
Eric Slud
References
Agresti, A. (2013) Categorical Data Analysis, 3rd edition, Wiley.
Examples
EHypMidP(30,c(50,80,120), 0.9)
AlphInts(30,c(50,80,120), lev=0.9)$CI.midP
EHypMidP(20, c(204,269,2016), 0.9)