model.prior

Internal function for prior weights.

internal

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

model.prior function

<dl><dt>model.size</dt>
<dd>Size of subset.</dd>
<dt>N.obs</dt>
<dd>Number of genetic variants.</dd>
<dt>prob.valid.inst</dt>
<dd>Probability (prior) of a genetic variant being a valid instrument.</dd></dl>

Arguments

Prior weight function — model.prior

<dl>

<dt>model.size</dt>
<dd>Size of subset.</dd>


<dt>N.obs</dt>
<dd>Number of genetic variants.</dd>


<dt>prob.valid.inst</dt>
<dd>Probability (prior) of a genetic variant being a valid instrument.</dd>

</dl>

Prior weight function

model.prior: Prior weight function

Description

Usage

Value

Arguments

Details

Examples