sizepower (version 1.42.0)

power.randomized: Power Calculation for Completely Randomized Treatment-Control Designs in Microarray studies

Description

This routine computes the individual power value for a completely randomized design with n treatment units and n control units (2n units in total). This power value is the expected fraction of truly differentially expressed genes that will be correctly declared as differentially expressed by the tests.

Usage

power.randomized(ER0, G0, absMu1, sigmad, n)

Arguments

ER0

mean number of false positives.

G0

anticipated number of genes in the experiment that are not differentially expressed.

absMu1

absolute mean difference in log-expression between treatment and control conditions as postulated under the alternative hypothesis H1.

sigmad

anticipated standard deviation of the difference in log-expression between treatment and control conditions. The relation between the standard deviation of the difference (sigmad) and the experimental error standard deviation (sigma) is sigmad=sqrt(2)/sigma.

n

the sample size for each group.

Value

• power
  power.
• psi1
  non-centrality parameter.

References

Lee, M.-L. T. (2004). Analysis of Microarray Gene Expression Data. Kluwer Academic Publishers, ISBN 0-7923-7087-2. Lee, M.-L. T., Whitmore, G. A. (2002). Power and sample size for DNA microarray studies. Statistics in Medicine, 21:3543-3570.

See Also

power.matched, power.multi, sampleSize.randomized, sampleSize.matched

Examples

power.randomized(ER0=2, G0=5000, absMu1=1, sigmad=0.5657, n=8)