power.prop.test

0th

Percentile

Power Calculations for Two-Sample Test for Proportions

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

Keywords
htest
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.

Note that not all conditions can be satisfied, e.g., for

power.prop.test(n=30, p1=0.90, p2=NULL, power=0.8, strict=TRUE)

there is no proportion p2 between p1 = 0.9 and 1, as you'd need a sample size of at least \(n = 74\) to yield the desired power for \((p1,p2) = (0.9, 1)\).

For these impossible conditions, currently a warning (warning) is signalled which may become an error (stop) in the future.

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 p1 and p2 is computed, then \(p1 < p2\) is assumed and will hold, but if you specify both, \(p2 \le p1\) is allowed.

See Also

prop.test, uniroot

Aliases
  • power.prop.test
Examples
library(stats) # NOT RUN { 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 try( power.prop.test(n=30, p1=0.90, p2=NULL, power=0.8) ) # a warning (which may become an error) ## Reason: power.prop.test( p1=0.90, p2= 1.0, power=0.8) ##-> n = 73.37 # }
Documentation reproduced from package stats, version 3.5.0, License: Part of R 3.5.0

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