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 individual level. Existing tools for the analysis of spatial data in R may appear too complex to non-specialists which may 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 with a measure of uncertainty is made available to non specialists.

翻译：作为使用行政区域评估小区域健康不平等的替代方案，Sauzet等人提出采用以自我为中心的方法，在个体层面建模健康结果的空间相关结构。现有用于R语言空间数据分析的工具对非专业人员而言可能过于复杂，从而限制了该方法的推广使用。我们推出了R软件包EgoCor，该软件包提供用户友好界面，通过单一函数展示一系列图形和参数表格，以便于决策哪种指数参数最适合原始数据或残差。该函数基于R软件包gstat中的函数构建。此外，我们还实现了一个提供Dyck与Sauzet提出的不确定性度量函数。借助R软件包EgoCor，非专业人员也能对健康结果的空间相关结构进行建模并获取不确定性度量。