.biweight_midvar

Compute a robust estimate of midvariance using the biweight method, which reduces the influence of outliers by applying a weighting function to the data based on their deviation from a central value.

Provides a comprehensive framework for batch effect diagnostics, harmonization, and post-harmonization downstream analysis. Features include interactive visualization tools, robust statistical tests, and a range of harmonization techniques. Additionally, 'ComBatFamQC' enables the creation of life-span age trend plots with estimated age-adjusted centiles and facilitates the generation of covariate-corrected residuals for analytical purposes. Methods for harmonization are based on approaches described in Johnson et al., (2007) <doi:10.1093/biostatistics/kxj037>, Beer et al., (2020) <doi:10.1016/j.neuroimage.2020.117129>, Pomponio et al., (2020) <doi:10.1016/j.neuroimage.2019.116450>, and Chen et al., (2021) <doi:10.1002/hbm.25688>.

Zheng Ren

ComBatFamQC

Comprehensive Batch Effect Diagnostics and Harmonization

Andrew Chen

Elizabeth Horwath

.biweight_midvar function

<dl><dt>data</dt>
<dd>A numeric vector containing the data points for which the biweight midvariance is to be calculated.</dd>
<dt>center</dt>
<dd>An optional parameter specifying the central location of the data. If not provided, the function defaults to using the median of the data.</dd>
<dt>norm.unbiased</dt>
<dd>A logical parameter (default: <code>TRUE</code>) indicating whether to use a normalization constant for unbiased estimation. When <code>TRUE</code>, the constant is adjusted to 9 divided by the quantile function of 0.75 from the standard normal distribution.</dd></dl>

Arguments

Biweight Midvariance Calculation — .biweight_midvar

<dl>

<dt>data</dt>
<dd>A numeric vector containing the data points for which the biweight midvariance is to be calculated.</dd>


<dt>center</dt>
<dd>An optional parameter specifying the central location of the data. If not provided, the function defaults to using the median of the data.</dd>


<dt>norm.unbiased</dt>
<dd>A logical parameter (default: <code>TRUE</code>) indicating whether to use a normalization constant for unbiased estimation. When <code>TRUE</code>, the constant is adjusted to 9 divided by the quantile function of 0.75 from the standard normal distribution.</dd>

</dl>

.biweight_midvar: Biweight Midvariance Calculation

Description

Usage

Value

Arguments

Examples