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).

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)


[Package CooccurrenceAffinity version 1.0 Index]