DIVW-class

An object containing the estimate produced using the debiased inverse-variance weighted (dIVW) method as well as various statistics.

Encodes several methods for performing Mendelian randomization
analyses with summarized data. Summarized data on genetic associations with the
exposure and with the outcome can be obtained from large consortia. These data
can be used for obtaining causal estimates using instrumental variable methods.

Stephen Burgess

MendelianRandomization

Mendelian Randomization Package

Olena Yavorska

James Staley

Fernando Hartwig

Jim Broadbent

Christopher Foley

Andrew Grant

Amy Mason

Ting Ye

Haoran Xue

Zhaotong Lin

Siqi Xu

Ashish Patel

Hyunseung Kang

Sheng Wang

Ville Karhunen

DIVW-class function

<dl>
<dt><code>Over.dispersion</code></dt>
<dd>Should the method consider overdispersion (balanced horizontal pleiotropy)? Default is TRUE.</dd></dl>
<dt><code>Exposure</code></dt>
<dd>The name of the exposure variable.</dd>
<dt><code>Outcome</code></dt>
<dd>The name of the outcome variable.</dd>
<dt><code>Estimate</code></dt>
<dd>The causal point estimate from the median-based method.</dd>
<dt><code>StdError</code></dt>
<dd>The standard error associated with <code>Estimate</code> (obtained from bootstrapping).</dd>
<dt><code>CILower</code></dt>
<dd>The lower bound of the confidence interval for <code>Estimate</code> based on <code>StdError</code>.</dd>
<dt><code>CIUpper</code></dt>
<dd>The upper bound of the confidence interval for <code>Estimate</code> based on <code>StdError</code>.</dd>
<dt><code>Alpha</code></dt>
<dd>The significance level used in constructing the confidence interval (default is 0.05).</dd>
<dt><code>Pvalue</code></dt>
<dd>P-value associated with the causal estimate from the Wald method.</dd>
<dt><code>SNPs</code></dt>
<dd>The number of SNPs that used in the calculation.</dd>
<dt><code>Condition</code></dt>
<dd>A measure defined as (average F-statistic -1)*sqrt(# snps) that needs to be large for reliable asymptotic approximation based on the dIVW estimator. It is recommended to be greater than 20.</dd>

Slots

DIVW Class — DIVW-class

<dl>
<dt><code>Over.dispersion</code></dt>
<dd>Should the method consider overdispersion (balanced horizontal pleiotropy)? Default is TRUE.</dd>


<dt><code>Exposure</code></dt>
<dd>The name of the exposure variable.</dd>


<dt><code>Outcome</code></dt>
<dd>The name of the outcome variable.</dd>


<dt><code>Estimate</code></dt>
<dd>The causal point estimate from the median-based method.</dd>


<dt><code>StdError</code></dt>
<dd>The standard error associated with <code>Estimate</code> (obtained from bootstrapping).</dd>


<dt><code>CILower</code></dt>
<dd>The lower bound of the confidence interval for <code>Estimate</code> based on <code>StdError</code>.</dd>


<dt><code>CIUpper</code></dt>
<dd>The upper bound of the confidence interval for <code>Estimate</code> based on <code>StdError</code>.</dd>


<dt><code>Alpha</code></dt>
<dd>The significance level used in constructing the confidence interval (default is 0.05).</dd>


<dt><code>Pvalue</code></dt>
<dd>P-value associated with the causal estimate from the Wald method.</dd>


<dt><code>SNPs</code></dt>
<dd>The number of SNPs that used in the calculation.</dd>


<dt><code>Condition</code></dt>
<dd>A measure defined as (average F-statistic -1)*sqrt(# snps) that needs to be large for reliable asymptotic approximation based on the dIVW estimator. It is recommended to be greater than 20.</dd>


</dl>

DIVW Class

DIVW-class: DIVW Class

Description

Arguments

Slots