A functional-model-adjusted spatial scan statistic.

Abstract:

:This paper introduces a new spatial scan statistic designed to adjust cluster detection for longitudinal confounding factors indexed in space. The functional-model-adjusted statistic was developed using generalized functional linear models in which longitudinal confounding factors were considered to be functional covariates. A general framework was developed for application to various probability models. Application to a Poisson model showed that the new method is equivalent to a conventional spatial scan statistic that adjusts the underlying population for covariates. In a simulation study with single and multiple covariate models, we found that our new method adjusts the cluster detection procedure more accurately than other methods. Use of the new spatial scan statistic was illustrated by analyzing data on premature mortality in France over the period from 1998 to 2013, with the quarterly unemployment rate as a longitudinal confounding factor.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Ahmed MS,Genin M

doi

10.1002/sim.8459

subject

Has Abstract

pub_date

2020-04-15 00:00:00

pages

1025-1040

issue

8

eissn

0277-6715

issn

1097-0258

journal_volume

39

pub_type

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