vim.approxPval: Approximate P-Value Based Importance Measure

In holgerschw/logicFS: Identification of SNP Interactions

Description

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

Usage

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, [e-mail]

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

holgerschw/logicFS documentation built on April 15, 2020, 10:42 p.m.