# pruns.exact: Exact cumulative distribution function of runs test In randomizeBE: Create a Random List for Crossover Studies

## Description

This function calculates the exact cumulative conditional distribution of the Wald-Wolfowitz runs.

## Usage

 `1` ```pruns.exact(r, n1, n2, tail = c("2-sided", "lower", "upper")) ```

## Arguments

 `r` Number of runs observed. `n1` Number of +1 items in the sequence. `n2` Number of -1 items in the sequence. `tail` Tail of the cumulative distribution function. Default is the 2-tailed value.

## Value

Numeric value of the cumulative distribution function according to the chosen tail.

## Note

The 2-sided exact p-value is defined as P(abs(R-E(R)>=abs(r-E(R)).
The lower (left) tail p-value is defined as P(R<=r).
The upper (right) tail p-value is defined as P(R>=r).
r is the observed value of the random variable R.

D. Labes

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```# SPSS "Exact Tests": small sample example, exact p: 0.071 # x <- c(1, 1, 1, 1, 0, 0, 0, 0, 1, 1) pruns.exact(r=3, n1=4, n2=6) # 0.07142857 # left tail P(R<=3)=0.04761905 pruns.exact(r=3, n1=4, n2=6, tail="lower") # right tail P(R>=3)=0.9904762 pruns.exact(r=3, n1=4, n2=6, tail="upper") # or via runs.pvalue (2-sided) x <- c(1, 1, 1, 1, 0, 0, 0, 0, 1, 1) runs.pvalue(x, pmethod="ex") ```

randomizeBE documentation built on May 30, 2017, 3:20 a.m.