gGlobalAncova: Generalized GlobalAncova group test

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

View source: R/gGlobalAncova.R

Description

Computation of a permutation test for the association between sets of variables (e.g. genes, SNPs, ...) and clinical entities. The variables can be continuous, binary, categorical, ordinal, or of mixed types. The test is carried out by comparing the deviances of the full generalized linear model and the reduced model lacking the design parameters of interest. The variable-wise models are summarized to a global test statistic for the complete set.

Usage

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gGlobalAncova(data, formula.full, formula.red=~1, model.dat, Sets, sumstat=sum, perm=10000)

Arguments

data

data.frame of variables to be tested in sets (columns=variables); (multi-) categorical variables should be factors, ordinal variables should be ordered factors

formula.full

model formula for the full model

formula.red

model formula for the reduced model (that does not contain the terms of interest)

model.dat

data.frame of regressors, containing variables specified in formula.full and formula.red

Sets

vector of names or indices of variables or list of those, defining sets of variables

sumstat

function for summarizing univariate test statistics; default is sum

perm

number of permutations

Value

A data.frame with test statistic and p-value for each tested set.

Note

The test is fast for categorical data and categorical design variable. For other types of variables and more complex designs it is rather slow.

This work was supported by BMBF grant 01ZX1309B, Germany.

Author(s)

Reinhard Meister meister@beuth-hochschule.de
Manuela Hummel m.hummel@dkfz.de

See Also

GlobalAncova

Examples

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data(bindata)
gGlobalAncova(bindata[,-1], formula.full = ~group, model.dat = bindata, perm = 1000)

GlobalAncova documentation built on Nov. 8, 2020, 8:10 p.m.