awot_null

A flexible and robust joint test of the single nucleotide polymorphism (SNP) main effect and genotype-by-treatment interaction effect for continuous and binary endpoints. Two analytic procedures, Cauchy weighted joint test (CWOT) and adaptively weighted joint test (AWOT), are proposed to accurately calculate the joint test p-value. The proposed methods are evaluated through extensive simulations under various scenarios. The results show that the proposed AWOT and CWOT control type I error well and outperform existing methods in detecting the most interesting signal patterns in pharmacogenetics (PGx) association studies. For reference, see Hong Zhang, Devan Mehrotra and Judong Shen (2022) <doi:10.13140/RG.2.2.28323.53280>.

Hong Zhang

cwot

Cauchy Weighted Joint Test for Pharmacogenetics Analysis

awot_null function

<dl><dt>y</dt>
<dd>- Continuous response variable.</dd>
<dt>tr</dt>
<dd>- Binary treatment variable, 1 for treated, 0 for placebo.</dd>
<dt>x</dt>
<dd>- Covariates in addition to treatment variable.</dd></dl>

Arguments

Prepare null model for awot. — awot_null

<dl>

<dt>y</dt>
<dd>- Continuous response variable.</dd>


<dt>tr</dt>
<dd>- Binary treatment variable, 1 for treated, 0 for placebo.</dd>


<dt>x</dt>
<dd>- Covariates in addition to treatment variable.</dd>

</dl>

awot_null: Prepare null model for awot.

Description

Usage

Value

Arguments

References

Examples