no.reps {dae}  R Documentation 
Computes the number of replicates for an experiment
Description
Computes the number of pure replicates required in an experiment to achieve a specified power.
Usage
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)
Arguments
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 

Value
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.
Author(s)
Chris Brien
See Also
power.exp
, detect.diff
in package dae.
Examples
## 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)