no.reps | R Documentation |
Computes the number of pure replicates required in an experiment to achieve a specified power.
no.reps(multiple=1., df.num=1.,
df.denom=expression((df.num + 1.) * (r - 1.)), delta=1.,
sigma=1., alpha=0.05, power=0.8, tol=0.1, print=FALSE)
multiple |
The multiplier, m, which when multiplied by the number of pure replicates of a treatment, r, gives the number of observations rm used in computing means for some, not necessarily proper, subset of the treatment factors; m is the replication arising from other treatment factors. However, for single treatment factor experiments the subset can only be the treatment factor and m = 1. |
df.num |
The degrees of freedom of the numerator of the F for testing the term involving the treatment factor subset. |
df.denom |
The degrees of freedom of the denominator of the F for testing the term involving the treatment factor subset. |
delta |
The true difference between a pair of means for some, not necessarily proper, subset of the treatment factors. |
sigma |
The population standard deviation. |
alpha |
The significance level to be used. |
power |
The minimum power to be achieved. |
tol |
The maximum difference tolerated between the power required and the power computed in determining the number of replicates. |
print |
|
A list containing nreps
, a single numeric
value containing the computed number of pure replicates, and power
, a single numeric
value containing the power for the computed number of pure replicates.
Chris Brien
power.exp
, detect.diff
in package dae.
## Compute the number of replicates (blocks) required for a randomized
## complete block design with four treatments.
no.reps(multiple = 1, df.num = 3,
df.denom = expression(df.num * (r - 1)), delta = 5,
sigma = sqrt(20), print = TRUE)
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