SchurC

Calculates the efficient information \(I_{bb}-I_{ba}I_{aa}^{-1}I_{ab}\).

Inverse normal transformation (INT) based genetic association testing. These tests are recommend for continuous traits with non-normally distributed residuals. INT-based tests robustly control the type I error in settings where standard linear regression does not, as when the residual distribution exhibits excess skew or kurtosis. Moreover, INT-based tests dominate standard linear regression in terms of power. These tests may be classified into two types. In direct INT (D-INT), the phenotype is itself transformed. In indirect INT (I-INT), phenotypic residuals are transformed. The omnibus test (O-INT) adaptively combines D-INT and I-INT into a single robust and statistically powerful approach. See McCaw ZR, Lane JM, Saxena R, Redline S, Lin X. "Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies" <doi:10.1111/biom.13214>.

Zachary McCaw

RNOmni

Rank Normal Transformation Omnibus Test

SchurC function

<dl><dt>Ibb</dt>
<dd>Information of target parameter</dd>
<dt>Iaa</dt>
<dd>Information of nuisance parameter</dd>
<dt>Iba</dt>
<dd>Cross information between target and nuisance parameters</dd></dl>

Arguments

Schur complement — SchurC

<dl>

<dt>Ibb</dt>
<dd>Information of target parameter</dd>


<dt>Iaa</dt>
<dd>Information of nuisance parameter</dd>


<dt>Iba</dt>
<dd>Cross information between target and nuisance parameters</dd>

</dl>

SchurC: Schur complement

Description

Usage

Value

Arguments