Literature DB >> 7582201

Second-order analysis of space-time clustering.

P J Diggle1, A G Chetwynd, R Häggkvist, S E Morris.   

Abstract

We consider the problem of detecting and describing space-time interaction in point process data. We extend existing second-order methods for purely spatial point process data to the spatial-temporal setting. This extension allows us to estimate space-time interaction as a function of spatial and temporal separation, and provides a useful reinterpretation of a popular test, due to Knox, for space-time interaction. Applications to simulated and real data indicate the method's potential.

Mesh：

Year:  1995        PMID： 7582201     DOI： 10.1177/096228029500400203

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN： 0962-2802            Impact factor:   3.021


  37 in total

Review 1.  Clusters and clustering of childhood cancer: a review.

Authors:  F E Alexander
Journal:  Eur J Epidemiol       Date:  1999-10       Impact factor: 8.082

2.  Revealing the microscale spatial signature of dengue transmission and immunity in an urban population.

Authors:  Henrik Salje; Justin Lessler; Timothy P Endy; Frank C Curriero; Robert V Gibbons; Ananda Nisalak; Suchitra Nimmannitya; Siripen Kalayanarooj; Richard G Jarman; Stephen J Thomas; Donald S Burke; Derek A T Cummings
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-29       Impact factor: 11.205

3.  Inference of cowpox virus transmission rates between wild rodent host classes using space-time interaction.

Authors:  David Carslake; Malcolm Bennett; Sarah Hazel; Sandra Telfer; Michael Begon
Journal:  Proc Biol Sci       Date:  2006-04-07       Impact factor: 5.349

4.  Space-time clustering of elevated thyroid stimulating hormone levels.

Authors:  Mark S Pearce; Richard J Q McNally; Julie Day; S Murthy Korada; Steve Turner; Tim D Cheetham
Journal:  Eur J Epidemiol       Date:  2011-04-08       Impact factor: 8.082

Review 5.  A review of spatial methods in epidemiology, 2000-2010.

Authors:  Amy H Auchincloss; Samson Y Gebreab; Christina Mair; Ana V Diez Roux
Journal:  Annu Rev Public Health       Date:  2012-04       Impact factor: 21.981

6.  Space-time analysis of hospitalised dengue patients in rural Thailand reveals important temporal intervals in the pattern of dengue virus transmission.

Authors:  Jared Aldstadt; In-Kyu Yoon; Darunee Tannitisupawong; Richard G Jarman; Stephen J Thomas; Robert V Gibbons; Angkana Uppapong; Sopon Iamsirithaworn; Alan L Rothman; Thomas W Scott; Timothy Endy
Journal:  Trop Med Int Health       Date:  2012-07-19       Impact factor: 2.622

7.  Space-time clustering of childhood lymphatic leukaemias and non-Hodgkin's lymphomas in Sweden.

Authors:  B Gustafsson; J Carstensen
Journal:  Eur J Epidemiol       Date:  2000       Impact factor: 8.082

8.  Space-time clustering of glioma cannot be attributed to specific histological subgroups.

Authors:  M P W A Houben; J W W Coebergh; J M Birch; C C Tijssen; C M van Duijn; R J Q McNally
Journal:  Eur J Epidemiol       Date:  2006       Impact factor: 8.082

9.  Space-time clustering analyses of testicular cancer amongst 15-24-year-olds in Northern England.

Authors:  R J Q McNally; M S Pearce; L Parker
Journal:  Eur J Epidemiol       Date:  2006       Impact factor: 8.082

10.  Space-time clustering analyses of type 1 diabetes among 0- to 29-year-olds in Yorkshire, UK.

Authors:  R J Q McNally; R G Feltbower; L Parker; H J Bodansky; F Campbell; P A McKinney
Journal:  Diabetologia       Date:  2006-03-24       Impact factor: 10.122
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