A simulation study on specifying a regression model for spatial data: choosing between heterogeneity and autocorrelation effects

A - Papers appearing in refereed journals

Harris, P. 2019. A simulation study on specifying a regression model for spatial data: choosing between heterogeneity and autocorrelation effects. Geographical Analysis . 51 (2), pp. 151-181. https://doi.org/10.1111/gean.12163

AuthorsHarris, P.

In this simulation study, regressions specified with autocorrelation effects are compared against those with relationship heterogeneity effects, and in doing so, provides guidance on their use. Regressions investigated are: (1) multiple linear regression, (2) a simultaneous autoregressive error model, and (3) geographically weighted regression. The first is nonspatial and acts as a control, the second accounts for stationary spatial autocorrelation via the error term, while the third captures spatial heterogeneity through the modeling of nonstationary relationships between the response and predictor variables. The geostatistical‐based simulation experiment generates data and coefficients with known multivariate spatial properties, all within an area‐unit spatial setting. Spatial autocorrelation and spatial heterogeneity effects are varied and accounted for. On fitting the regressions, that each have different assumptions and objectives, to very different geographical processes, valuable insights to their likely performance are uncovered. Results objectively confirm an inherent interrelationship between autocorrelation and heterogeneity, that results in an identification problem when choosing one regression over another. Given this, recommendations on the use and implementation of these spatial regressions are suggested, where knowledge of the properties of real study data and the analytical questions being posed are paramount.

Year of Publication2019
JournalGeographical Analysis
Journal citation51 (2), pp. 151-181
Digital Object Identifier (DOI)https://doi.org/10.1111/gean.12163
Open accessPublished as ‘gold’ (paid) open access
FunderBBSRC Newton funding
Biotechnology and Biological Sciences Research Council
Funder project or codeS2N - Soil to Nutrition - Work package 2 (WP2) - Adaptive management systems for improved efficiency and nutritional quality
The North Wyke Farm Platform- National Capability [2017-22]
Publisher's version
Output statusPublished
Publication dates
Online22 May 2018
Publication process dates
Accepted09 Mar 2018
Copyright licenseCC BY

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