Brunsdon, Chris and Charlton, Martin
(2011)
An assessment of the effectiveness of multiple hypothesis
testing for geographical anomaly detection.
Environment and Planning B: Planning and Design, 38 (2).
pp. 216-230.
ISSN 0265-8135
Abstract
The practice of multiple significance testing is reviewed, and an alternative to the frequently
used Bonferroni correction is considered. Rather than controlling the family-wise error rate (FWER)
ˆ
the probability of a false positive in
any
of the significance tests
ˆ
this alternative due to Benjamini
and Hochberg controls the false discovery rate (FDR). This is the proportion of tests reporting a
significant result that are actually `false alarms'. The methods (and some variants) are demonstrated
on a procedure to detect clusters of full-time unpaid carers based on UK census data, and are also
assessed using simulation. Simulation results show that the FDR-based corrections are typically more
powerful than FWER-based ones, and also that the degree of conservatism in FWER-based proce-
dures is quite extreme, to the extent that the standard Bonferroni procedure intended to constrain the
FWER to be below 0.05 actually has a FWER of around
6 X 10 -5
. We conclude that in situations
where one is scanning for anomalies, the extreme conservatism of FWER-based approaches results in
a lack of power, and that FDR-based approaches are more appropriate
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