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dae (version 3.0-32)

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)

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.

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.

See Also

power.exp, detect.diff in package dae.

Examples

Run this code
# NOT RUN {
## 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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