Power calculations for t-tests of means (one sample, two samples and paired samples)

Description

Compute power of tests or determine parameters to obtain target power (similar to power.t.test).

Usage

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pwr.t.test(n = NULL, d = NULL, sig.level = 0.05, power = NULL, 
    type = c("two.sample", "one.sample", "paired"),
    alternative = c("two.sided", "less", "greater"))

Arguments

n

Number of observations (per sample)

d

Effect size

sig.level

Significance level (Type I error probability)

power

Power of test (1 minus Type II error probability)

type

Type of t test : one- two- or paired-samples

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less"

Details

Exactly one of the parameters 'd','n','power' and 'sig.level' must be passed as NULL, and that parameter is determined from the others. Notice that the last one has non-NULL default so NULL must be explicitly passed if you want to compute it.

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.

Author(s)

Stephane Champely <champely@univ-lyon1.fr> but this is a mere copy of Peter Dalgaard work (power.t.test)

References

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale,NJ: Lawrence Erlbaum.

See Also

power.prop.test

Examples

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## One sample (power)
## Exercise 2.5 p. 47 from Cohen (1988)
pwr.t.test(d=0.2,n=60,sig.level=0.10,type="one.sample",alternative="two.sided")

## Paired samples (power)
## Exercise p. 50 from Cohen (1988)
d<-8/(16*sqrt(2*(1-0.6)))
pwr.t.test(d=d,n=40,sig.level=0.05,type="paired",alternative="two.sided")

## Two independent samples (power)
## Exercise 2.1 p. 40 from Cohen (1988)
d<-2/2.8
pwr.t.test(d=d,n=30,sig.level=0.05,type="two.sample",alternative="two.sided")

## Two independent samples (sample size)
## Exercise 2.10 p. 59
pwr.t.test(d=0.3,power=0.75,sig.level=0.05,type="two.sample",alternative="greater")