loglikelihoodcorrel

Internal function for calculating log-likelihood for for maximum-likelihood method.

internal

Encodes several methods for performing Mendelian randomization analyses with summarized data. Similar to the 'MendelianRandomization' package, but with fewer bells and whistles, and less frequent updates. As described in Yavorska (2017) <doi:10.1093/ije/dyx034> and Broadbent (2020) <doi:10.12688/wellcomeopenres.16374.2>.

Stephen Burgess

MRZero

Diet Mendelian Randomization

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

loglikelihoodcorrel function

<dl><dt>param</dt>
<dd>Parameters in the model.</dd>
<dt>x</dt>
<dd>Genetic associations with the exposure.</dd>
<dt>Taux</dt>
<dd>Precision matrix for associations with the exposure.</dd>
<dt>y</dt>
<dd>Genetic associations with the outcome.</dd>
<dt>Tauy</dt>
<dd>Precision matrix for associations with the outcome.</dd></dl>

Arguments

Calculates log-likelihood with correlated variants in two-sample setting (no correlation from sample overlap) — loglikelihoodcorrel

<dl>

<dt>param</dt>
<dd>Parameters in the model.</dd>


<dt>x</dt>
<dd>Genetic associations with the exposure.</dd>


<dt>Taux</dt>
<dd>Precision matrix for associations with the exposure.</dd>


<dt>y</dt>
<dd>Genetic associations with the outcome.</dd>


<dt>Tauy</dt>
<dd>Precision matrix for associations with the outcome.</dd>

</dl>

Calculates log-likelihood with correlated variants in two-sample setting (no correlation from sample overlap)

loglikelihoodcorrel: Calculates log-likelihood with correlated variants in two-sample setting (no correlation from sample overlap)

Description

Usage

Value

Arguments

Details