f: A function to compute adjustments for the effct of covariates...
In clippda: A package for the clinical proteomic profiling data analysis

Description Usage Arguments Value Author(s) References See Also Examples

A function to compute the Z values when planning an experiment with a binary exposure and a binary confounder. You input the probabilities of 3-cells of the resulting multinomial distribution.

1	f(x, y, z)

`x`	Proportion of elements in cell 1 of a multinomial population with four cells.
`y`	Proportion of elements in cell 2 of a multinomial population with four cells.
`z`	Proportion of elements in cell 1 of a multinomial population with four cells. The z here is different from the Z which contains information on the effect of covariates and data imbalance on sample size.

It returns a single real number (greater than or equal 2), representing Z.

Stephen Nyangoma

Nyangoma SO, Ferreira JA, Collins SI, Altman DG, Johnson PJ, and Billingham LJ: Sample size calculations for planning clinical proteomic profiling studies using mass spectrometry. (Working paper)

The function ZvaluesformultinomialPlots

# for a 1:1:1:1 experiment
x=.25;y=.25;z=.25

# compute Z
Z=f(x,y,z)
Z
## The function is currently defined as
function (x,y,z) {
Z=(1-x-z)*(x+y)/(2*(((1-x-z)*(1-x-y)*(1-y-z))-(1-x-y-z)^2))
Z
  }