confounders_clsq {structToolbox} | R Documentation

## Check for confounding factors in ttest

### Description

Compares the coefficients for a ttest without including confounding factors to models with confounding factor included. Currently only ttest is supported.

### Usage

    confounders_clsq(
      alpha = 0.05,
      mtc = "fdr",
      factor_name,
      confounding_factors,
      threshold = 0.15,
      ...
    )

### Arguments

`alpha` | p-value threshold for determining significance. Default alpha = 0.05.
`mtc` | multiple test correction method to apply. Can be: holm, hochberg, hommel, bonferroni, BH, BY, fdr or [none]
`factor_name` | the column name of sample_meta to use in regression
`confounding_factors` | the column names of factors potentially confounding with the main factor if interest
`threshold` | the threshold (between 0 and 1) for accepting a factor as confounding
`...` | additional slots and values passed to struct_class

### Value

A struct model object with functions for applying classical least squares

struct object

### Examples

    D = MTBLS79_DatasetExperiment()
    M = filter_by_name(mode='include',dimension='variable',
            names=colnames(D$data)[1:10]) + # first 10 features
        filter_smeta(mode='exclude',levels='QC',
            factor_name='class') + # reduce to two group comparison
        confounders_clsq(factor_name = 'class',
            confounding_factors=c('sample_order','batch'))
    M = model_apply(M,D)

[Package structToolbox version 1.0.1 Index]