t-Test Design
If you are designing an experiment in which you will use a
t-test to check the significance of the results (typically, an experiment
in which you calculate the mean value of a random variable for a “test” population and a
“control” population), then you can use the power.t.test
function to help design the experiment:
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)
For this function, n
specifies
the number of observations (per group); delta
is the true difference in means between
the groups; sd
is the true standard
deviation of the underlying distribution; sig.level
is the significance level (Type I
error probability); power
is the power
of the test (1 − Type II error probability); type
specifies whether the test is one sample,
two sample, or paired; alternative
specifies whether the test is one or two sided; and strict
specifies whether to use a strict
interpretation in the two-sided case. This function will calculate either
n
, delta
, sig.level
, sd
, or power
,
depending on the input. You must specify at least four of these
parameters: n
, delta
, sd
,
sig.level
, power
. The remaining argument must be null; this
is the value that the function calculates.
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