The Multiple Testing Issue in Geographically Weighted Regression

Alan Ricardo da Silva, Stewart Fotheringham

Research output: Contribution to journalArticlepeer-review

106 Scopus citations


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.

Original languageEnglish (US)
JournalGeographical Analysis
StateAccepted/In press - 2015

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth-Surface Processes


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