power.prop.test {stats} | R Documentation

## Power Calculations for Two-Sample Test for Proportions

### Description

Compute the power of the two-sample test for proportions, or determine parameters to obtain a target power.

### Usage

    power.prop.test(n = NULL, p1 = NULL, p2 = NULL, sig.level = 0.05,
                    power = NULL,
                    alternative = c("two.sided", "one.sided"),
                    strict = FALSE, tol = .Machine$double.eps^0.25)

### Arguments

`n` | number of observations (per group)
`p1` | probability in one group
`p2` | probability in other group
`sig.level` | significance level (Type I error probability)
`power` | power of test (1 minus Type II error probability)
`alternative` | one- or two-sided test. Can be abbreviated.
`strict` | use strict interpretation in two-sided case
`tol` | numerical tolerance used in root finding, the default providing (at least) four significant digits.

### Details

Exactly one of the parameters `n`, `p1`, `p2`, `power`, and `sig.level` must be passed as NULL, and that parameter is determined from the others. Notice that `sig.level` has a non-NULL default so NULL must be explicitly passed if you want it computed.

If `strict = TRUE` is used, the power will include the probability of rejection in the opposite direction of the true effect, in the two-sided case. Without this the power will be half the significance level if the true difference is zero.

### Value

Object of class `"power.htest"`, a list of the arguments (including the computed one) augmented with `method` and `note` elements.

### Note

`uniroot` is used to solve power equation for unknowns, so you may see errors from it, notably about inability to bracket the root when invalid arguments are given. If one of them is computed `p1 < p2` will hold, although this is not enforced when both are specified.

### Author(s)

Peter Dalgaard. Based on previous work by Claus Ekstrøm

### See Also

`prop.test`, `uniroot`

### Examples

    power.prop.test(n = 50, p1 = .50, p2 = .75)      ## => power = 0.740
    power.prop.test(p1 = .50, p2 = .75, power = .90) ## =>     n = 76.7
    power.prop.test(n = 50, p1 = .5, power = .90)    ## =>    p2 = 0.8026
    power.prop.test(n = 50, p1 = .5, p2 = 0.9, power = .90, sig.level=NULL)
                                                     ## => sig.l = 0.00131
    power.prop.test(p1 = .5, p2 = 0.501, sig.level=.001, power=0.90)
                                                     ## => n = 10451937

[Package stats version 3.3.0 Index]