power.t.test Power calculations for one and two sample t tests

Description

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

Usage

power.t.test(n = NULL, delta = NULL, sd = 1, sig.level = 0.05,
             power = NULL,
             type = c("two.sample", "one.sample", "paired"),
             alternative = c("two.sided", "one.sided"),
             strict = FALSE, tol = .Machine$double.eps^0.25)

Arguments

n

number of observations (per group)

delta

true difference in means

sd

standard deviation

sig.level

significance level (Type I error probability)

power

power of test (1 minus Type II error probability)

type

string specifying the type of t test. Can be abbreviated.

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, delta, power, sd, and sig.level must be passed as NULL, and that parameter is determined from the others. Notice that the last two have non-NULL defaults, so NULL must be explicitly passed if you want to compute them.

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 the power equation for unknowns, so you may see errors from it, notably about inability to bracket the root when invalid arguments are given.

Author(s)

Peter Dalgaard. Based on previous work by Claus Ekstrøm

See Also

t.test, uniroot

Examples

 power.t.test(n = 20, delta = 1)
 power.t.test(power = .90, delta = 1)
 power.t.test(power = .90, delta = 1, alternative = "one.sided")

Copyright (©) 1999–2012 R Foundation for Statistical Computing.
Licensed under the GNU General Public License.