Analyse problems, not data : One world, one health

Diggle, Peter J. (2018) Analyse problems, not data : One world, one health. Spatial Statistics, 28. pp. 4-7. ISSN 2211-6753

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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.

Item Type:
Journal Article
Journal or Publication Title:
Spatial Statistics
Additional Information:
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
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1900/1903
Subjects:
?? data modelleptospirosisprocess modelserial dilution assaycomputers in earth sciencesstatistics and probabilitymanagement, monitoring, policy and law ??
ID Code:
129139
Deposited By:
Deposited On:
13 Dec 2018 14:30
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Oct 2024 00:29