find.ncp {SharedHT2}R Documentation

Find non-centrality parameter

Description

In order to provide a yardstick in designing simulation experiments this function calculates the non-centrality parameter for a simple F test of the null hypothesis of zero group means

Usage

find.ncp(e.I, e.II, nreps, d)

Arguments

e.I type I error i.e. level of significance
e.II type II error i.e. 1-power
nreps # replicates
d # groups

Value

An numeric vector of length 2, containing the calculated effect-size and the corresponding power of the standard F test of the null hypothesis that all group means are zero at the alternative that each group has mean effect-size times the common within group standard deviation.

theta The effect size
power Corresponding power

Note

This is used to set up the true positives genes in the simulation routines by deciding which genes are ``true positives" in tests of the null that all groups means are zero. Each group is assigned a mean equal to $σ theta$ where $σ$ is the average common within group standard deviation and $theta$ is the effect size returned by a call to this function, for example $theta=2.0$ as in the example below. In calls to the simulation routine you only need to specify the per gene effect size as $σ$ is calculated internally in all cases. For example if you want the first 100 rows to be ``true-positives" in simulated micro-array data containing 15000 genes then in the simulation routines just specify ``effect.size=c(rep(es, 100), rep(0, 15000-100)" in the calls to simulation routines listed above. See the documentation for routines listed above in ``see also".

Author(s)

Grant Izmirlian izmirlian@nih.gov

See Also

SimNorm.IG, SimMVN.IW, SimMVN.mxIW

Examples

  
  find.ncp(0.005, 0.13179983, 3, 2)


[Package SharedHT2 version 2.0 Index]