covidfear

Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear.

A collection of Bayesian networks (discrete, Gaussian, and conditional linear Gaussian) collated from recent academic literature. The 'bnRep_summary' object provides an overview of the Bayesian networks in the repository and the package documentation includes details about the variables in each network. A Shiny app to explore the repository can be launched with 'bnRep_app()' and is available online at <https://manueleleonelli.shinyapps.io/bnRep>. Reference: 'M. Leonelli' (2025) <doi:10.1016/j.neucom.2025.129502>.

Manuele Leonelli

bnRep

A Repository of Bayesian Networks from the Academic Literature

covidfear function

A discrete Bayesian network to understand the effect of demographic factors on the answers to the COVID-19 fear scale and the relationship between the scale items. The Bayesian network was learned as in the referenced paper. The vertices are:<dl>
<dt>Age</dt>
<dd>(Young, Adult);</dd><dt>Gender</dt>
<dd>(Female, Male);</dd><dt>Fear</dt>
<dd>I am most afraid of COVID-19 (Disagree, Neither, Agree);</dd><dt>Think</dt>
<dd>It makes me uncomfortable to think about COVID-19 (Disagree, Neither, Agree);</dd><dt>Hands</dt>
<dd>My hands become clammy when I think about COVID-19 (Disagree, Neither, Agree);</dd><dt>Life</dt>
<dd>I fear losing my life because of COVID-19 (Disagree, Neither, Agree);</dd><dt>News</dt>
<dd>I become nervous or anxious when watching news and stories about COVID-19 on social media (Disagree, Neither, Agree);</dd><dt>Sleep</dt>
<dd>I cannot sleep because I am worried about getting COVID-19 (Disagree, Neither, Agree);</dd><dt>Hearth</dt>
<dd>My heart races or palpitates when I think about getting COVID-19 (Disagree, Neither, Agree);</dd>
</dl>

Format

covidfear Bayesian Network — covidfear

A discrete Bayesian network to understand the effect of demographic factors on the answers to the COVID-19 fear scale and the relationship between the scale items. The Bayesian network was learned as in the referenced paper. The vertices are:<dl>
<dt>Age</dt>
<dd>(Young, Adult);</dd>

<dt>Gender</dt>
<dd>(Female, Male);</dd>

<dt>Fear</dt>
<dd>I am most afraid of COVID-19 (Disagree, Neither, Agree);</dd>

<dt>Think</dt>
<dd>It makes me uncomfortable to think about COVID-19 (Disagree, Neither, Agree);</dd>

<dt>Hands</dt>
<dd>My hands become clammy when I think about COVID-19 (Disagree, Neither, Agree);</dd>

<dt>Life</dt>
<dd>I fear losing my life because of COVID-19 (Disagree, Neither, Agree);</dd>

<dt>News</dt>
<dd>I become nervous or anxious when watching news and stories about COVID-19 on social media (Disagree, Neither, Agree);</dd>

<dt>Sleep</dt>
<dd>I cannot sleep because I am worried about getting COVID-19 (Disagree, Neither, Agree);</dd>

<dt>Hearth</dt>
<dd>My heart races or palpitates when I think about getting COVID-19 (Disagree, Neither, Agree);</dd>


</dl>

covidfear: covidfear Bayesian Network

Description

Arguments

Value

Format

References