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The Multiple Testing Issue in Geographically Weighted Regression
Author(s) -
da Silva Alan Ricardo,
Fotheringham A. Stewart
Publication year - 2016
Publication title -
geographical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.773
H-Index - 65
eISSN - 1538-4632
pISSN - 0016-7363
DOI - 10.1111/gean.12084
Subject(s) - bonferroni correction , false discovery rate , false positive paradox , multiple comparisons problem , regression , computer science , false positives and false negatives , word error rate , statistics , geographically weighted regression , econometrics , data mining , artificial intelligence , mathematics , biology , biochemistry , gene
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.