The Multiple Testing Issue in Geographically Weighted Regression

Alan Ricardo da Silva · Alexander Stewart Fotheringham

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Spatial and Panel Data Analysis Geography Education and Pedagogy Statistical Methods and Applications

Abstract

This article describes the problem of multiple testing within a Geographically Weighted Regression framework and presents a possible solution to the problem which is based on a family‐wise error rate for dependent processes. We compare the solution presented here to other solutions such as the Bonferroni correction and the Byrne, Charlton, and Fotheringham proposal which is based on the Benjamini and Hochberg False Discovery Rate. We conclude that our proposed correction is superior to others and that generally some correction in the conventional t‐test is necessary to avoid false positives in GWR.

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References

1996The geography of parameter space: an investigation of spatial non-stationarity 1935Il calcolo delle assicurazioni su gruppi di teste 2003Geographically Weighted Regression 2007A systematic investigation of cross-validation in GWR model estimation: empirical analysis and Monte Carlo simulations

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