EgoCor: an R package to facilitate the use of exponential semi-variograms for modelling the local spatial correlation structure in social epidemiology

TL;DR

EgoCor is an R package designed to simplify modeling local spatial correlation in social epidemiology, making advanced geostatistical methods accessible to non-specialists through user-friendly tools.

Contribution

The paper introduces EgoCor, an R package that streamlines the application of exponential semi-variograms for spatial correlation analysis in social epidemiology.

Findings

Facilitates decision-making on exponential parameters

Provides uncertainty measures for spatial models

Enhances accessibility for non-specialists

Abstract

As an alternative to using administrative areas for the evaluation of small-area health inequalities, Sauzet et al. suggested to take an ego-centred approach and model the spatial correlation structure of health outcomes at the individual level. Existing tools for the analysis of spatial data in R might appear too complex to non-specialists which could limit the use of the approach. We present the R package EgoCor which offers a user-friendly interface displaying in one function a range of graphics and tables of parameters to facilitate the decision making about which exponential parameters fit best either raw data or residuals. This function is based on the functions of the R package gstat. Moreover, we implemented a function providing the measure of uncertainty proposed by Dyck and Sauzet. With the R package EgoCor the modelling of spatial correlation structure of health outcomes or spatially structured predictors of health with a measure of uncertainty is made available to non-specialists.