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    Rights statement: This is the author’s version of a work that was accepted for publication in Spatial Statistics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Spatial Statistics, 28, 2018 DOI: 10.1016/j.spasta.2018.10.003

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Analyse problems, not data: One world, one health

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
<mark>Journal publication date</mark>12/2018
<mark>Journal</mark>Spatial Statistics
Volume28
Number of pages4
Pages (from-to)4-7
Publication StatusPublished
Early online date29/10/18
<mark>Original language</mark>English

Abstract

The last fifty years or so have seen a transformational change in statistical methodology, from a discrete set of specific methods to a single, integrated paradigm. An early example is the seminal paper by Nelder and Wedderburn (1972) that introduced the unifying concept of the generalised linear model for independently replicated data. Later computational advances have stimulated a comparable unification for modelling data with various kinds of dependence, for example in time and/or in space. I argue that this transformation should encourage statistical scientists to change their focus from analysing data to solving problems. I give an example from an ongoing study of the acquisition of natural immunity to leptospirosis among slum-dwellers in northern Brazil.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Spatial Statistics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Spatial Statistics, 28, 2018 DOI: 10.1016/j.spasta.2018.10.003