Network Model with Application to Allergy Diseases

TL;DR

This paper introduces a new graphical model for understanding the comorbidity of allergic diseases, combining causal and dependency structures, and evaluates its stability on multicenter clinical data.

Contribution

It presents a novel, computationally efficient misspecified graphical model that captures dependencies between diseases and symptoms, with practical applicability.

Findings

Model accurately reflects disease dependencies

Bootstrap and jackknife confirm model stability

Applied successfully to multicenter allergy data

Abstract

We propose a new graphical model to describe the comorbidity of allergic diseases. We present our model in two versions. First, we introduce a generative model that correctly reflects the variables' causal relationship. Then we propose an approximation of the generative model by another misspecified model that is computationally more efficient and easily interpretable. We will focus on the misspecified version, which we consider more practical. We include in the model two directed graphs, one graph of known dependency between the main binary variables (diseases), and a second graph of the dependence between the occurrence of the diseases and their symptoms. In the model, we also consider additional auxiliary variables. The proposed model is evaluated on a cross-sectional multicentre study in Poland on the ECAP database (www.ecap.pl). An assessment of the stability of the proposed model was obtained using bootstrap and jackknife techniques.