Publication:
A simplified spatial+ approach to mitigate spatial confounding in multivariate spatial areal models

Date

2024

Director

Publisher

Elsevier
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113125RB-I00/ES/recolecta

Abstract

Spatial areal models encounter the well-known and challenging problem of spatial confounding. This issue makes it arduous to distinguish between the impacts of observed covariates and spatial random effects. Despite previous research and various proposed methods to tackle this problem, finding a definitive solution remains elusive. In this paper, we propose a simplified version of the spatial+ approach that involves dividing the covariate into two components. One component captures large-scale spatial dependence, while the other accounts for short-scale dependence. This approach eliminates the need to separately fit spatial models for the covariates. We apply this method to analyse two forms of crimes against women, namely rapes and dowry deaths, in Uttar Pradesh, India, exploring their relationship with socio-demographic covariates. To evaluate the performance of the new approach, we conduct extensive simulation studies under different spatial confounding scenarios. The results demonstrate that the proposed method provides reliable estimates of fixed effects and posterior correlations between different responses.

Description

Keywords

Crimes against women, M-models, Spatial confounding, Spatial+

Department

Estadística, Informática y Matemáticas / Estatistika, Informatika eta Matematika / Institute for Advanced Materials and Mathematics - INAMAT2

Faculty/School

Degree

Doctorate program

item.page.cita

Urdangarin, A., Goicoa, T., Kneib, T., Ugarte, M. D. (2024) A simplified spatial+ approach to mitigate spatial confounding in multivariate spatial areal models. Spatial Statistics, 59, 1-18. https://doi.org/10.1016/j.spasta.2023.100804.

item.page.rights

© 2024 The Authors. This is an open access article under the CC BY-NC-ND license.

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