# poibin.midp: Calculated the mid-p values based on the Poisson-Binomial... In tamartsi/BinomiRare: Test the association of rare variants with a disease

## Description

Given a vector of disease probabilities and a number of diseased individual, Calculated the mid-p values based on the Poisson-Binomial distribution

## Usage

 `1` ```poibin.midp(n.carrier, n.D.carrier, prob.vec) ```

## Arguments

 `n.carrier` The number of carriers of a rare variant `n.D.carrier` The number of diseased carriers of a rare variant. n.D.carrier cannot be larger than n.carrier. `prob.vec` vector of disease probabilities of the carriers.

## Value

a single numeric variable - a p-value for the test that the number n.D.carrier is consistent with prob.vec.

## Note

Althouth n.carrier is not strictly needed, but is useful for quality checks, especially when meta-analyzing.

Tamar Sofer

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```require(poibin) n <- 100 ### simulation under the null g <- rbinom(n, 2, 0.1) x <- rnorm(n) p <- expit(-2.3 + x) d <- rbinom(n, size = 1, prob = p) mod <- glm(d ~ x, family = "binomial") prob.d <- expit(predict(mod)) poibin.midp(n.carrier = sum(g >0 ), n.D.carrier = sum(g*d > 0), prob.vec = prob.d[which(g>0)] ) ##### under the alternative: p <- expit(-2.3 + x + g) d <- rbinom(n, size = 1, prob = p) mod <- glm(d ~ x, family = "binomial") prob.d <- expit(predict(mod)) poibin.midp(n.carrier = sum(g >0 ), n.D.carrier = sum(g*d > 0), prob.vec = prob.d[which(g>0)] ) ```

tamartsi/BinomiRare documentation built on May 27, 2017, 2:14 a.m.