Compute power of test, or determine parameters to obtain target power for equal and unequal sample sizes.
power_t_test(n = NULL, delta = NULL, sd = 1, sig.level = 0.05, power = NULL, ratio = 1, sd.ratio = 1, type = c("two.sample", "one.sample", "paired"), alternative = c("two.sided", "one.sided"), df.method = c("welch", "classical"), strict = FALSE)
| 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) |
| ratio | The ratio n2/n1 between the larger group and the smaller group. Should be a value equal to or greater than 1 since n2 is the larger group. Defaults to 1 (equal group sizes) |
| sd.ratio | The ratio sd2/sd1 between the standard deviations in the larger group and the smaller group. Defaults to 1 (equal standard deviations in the two groups) |
| type | Type of t test |
| alternative | One- or two-sided test |
| df.method | Method for calculating the degrees of default. Possibilities are welch (the default) or classical. |
| strict | Use strict interpretation in two-sided case |
Object of class power.htest, a list of the arguments (including the computed one)
augmented with method and note elements.
Exactly one of the parameters n, delta, power, sd, sig.level, ratio sd.ratio
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.
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.
power.t.test, power_prop_test, power.prop.test
power_t_test(delta=300, sd=450, power=.8, ratio=4)#> #> Two-sample t test power calculation with unequal sizes #> #> n = 23.37346, 93.49384 #> delta = 300 #> sd = 450 #> sig.level = 0.05 #> power = 0.8 #> alternative = two.sided #> #> NOTE: n is vector of number in each group #>