vim.approxPval: Approximate P-Value Based Importance Measure

Description Usage Arguments Value Author(s) References See Also

View source: R/vim.approxPval.R

Description

Computes the importances based on an approximation to a t- or F-distribution.

Usage

1
vim.approxPval(object, version = 1, adjust = "bonferroni")

Arguments

object

an object of class logicFS which contains the values of standardized importances. Only in the linear regression case, the importances in object are allowed to be non-standardized.

version

either 1 or 2. If 1, then the importance measure is computed by 1 - padj, where padj is the adjusted p-value. If 2, the importance measure is determined by -log10(padj), where a raw p-value equal to 0 is set to 1 / (10 * n.perm) to avoid infinitive importances.

adjust

character vector naming the method with which the raw permutation based p-values are adjusted for multiplicity. If "qvalue", the function qvalue.cal from the package siggenes is used to compute q-values. Otherwise, p.adjust is used to adjust for multiple comparisons. See p.adjust for all other possible specifications of adjust. If "none", the raw p-values will be used.

Value

An object of class logicFS containing the same object as object except for

vim

the values of the importance measure based on an approximation to the t- or F-distribution,

measure

the name of the used importance measure,

threshold

0.95 if version = 1, and -log10(0.05) if version = 2.

Author(s)

Holger Schwender, holger.schwender@hhu.de

References

Schwender, H., Ruczinski, I., Ickstadt, K. (2011). Testing SNPs and Sets of SNPs for Importance in Association Studies. Biostatistics, 12, 18-32.

See Also

logic.bagging, logicFS, vim.input, vim.set, vim.permSet


logicFS documentation built on Nov. 8, 2020, 5:23 p.m.