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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2309.12979 |
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| _version_ | 1866929339927363584 |
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| author | Dyck, Julia Koslik, Jan-Ole Sauzet, Odile |
| author_facet | Dyck, Julia Koslik, Jan-Ole Sauzet, Odile |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_12979 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | EgoCor: an R package to facilitate the use of exponential semi-variograms for modelling the local spatial correlation structure in social epidemiology Dyck, Julia Koslik, Jan-Ole Sauzet, Odile Computation 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. |
| title | EgoCor: an R package to facilitate the use of exponential semi-variograms for modelling the local spatial correlation structure in social epidemiology |
| topic | Computation |
| url | https://arxiv.org/abs/2309.12979 |