no.reps: 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)

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.

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: TRUE or FALSE to have or not have a table of power calculation details printed out.

Author

Chris Brien

Examples

Run this code

## 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)