Population shift bias in tests of space–time interaction

Computers, Environment and Urban Systems - Tập 36 - Trang 500-512 - 2012
Elizabeth A. Mack1, Nicholas Malizia1, Sergio J. Rey1
1School of Geographical Sciences and Urban Planning, Arizona State University, P.O. Box 875302, Tempe, AZ 85287-5302, USA

Tài liệu tham khảo

Adam, N., Janeja, V., & Atluri, V. (2004). Neighborhood based detection of anomalies in high dimension spatio-temporal sensor datasets. In Proceedings of the 2004 ACM Symposium on Applied Computing (pp. 576–583). Aldstadt, 2007, An incremental Knox test for the determination of the serial interval between successive cases of an infectious disease, Stochastic Environmental Research and Risk Assessment, 21, 487, 10.1007/s00477-007-0132-3 Alexander, 1992, Space–time clustering of childhood acute lymphoblastic leukaemia: Indirect evidence for a transmissible agent, British Journal of Cancer, 65, 589, 10.1038/bjc.1992.119 Alexander, 1998, Spatial temporal patterns in childhood leukaemia: Further evidence for an infectious origin, British Journal of Cancer, 77, 812, 10.1038/bjc.1998.132 Arribas-Bel, D., Koschinsky, J., & Amaral, P. (2011). Improving the multi-dimensional comparison of simulation results: A spatial visualization approach. GeoDa Center for Geospatial analysis and computation working paper 5. <http://geodacenter.asu.edu/category/public/improving-multi>. Baker, 1996, Testing for space–time clusters of unknown size, Journal of Applied Statistics, 23, 543, 10.1080/02664769624080 Birant, 2006, Spatio-temporal outlier detection in large databases, Journal of Computing and Information Technology, 14, 291, 10.2498/cit.2006.04.04 Birch, 2000, Space–time clustering patterns in childhood leukaemia support a role for infection, British Journal of Cancer, 82, 1571 Bowers, 2005, Domestic burglary repeats and space–time clusters, European Journal of Criminology, 2, 67, 10.1177/1477370805048631 Buuren, 1998, Space–time clustering of multiple sclerosis cases around birth, Acta Neurologica Scandinavica, 97, 351, 10.1111/j.1600-0404.1998.tb05965.x Chadee, 2005, Impact of vector control on a dengue fever outbreak in Trinidad, West Indies, in 1998, Tropical Medicine & International Health, 10, 748, 10.1111/j.1365-3156.2005.01449.x Chen, 2008, On detecting spatial outliers, GeoInformatica, 12, 455, 10.1007/s10707-007-0038-8 Chen, 1984, A study of three techniques for time–space clustering in Hodgkin’s disease, Statistics in Medicine, 3, 173, 10.1002/sim.4780030210 David, 1966, Two space–time interaction tests for epidemicity, British Journal of Preventive & Social Medicine, 20, 44 De Smith, 2006 Diggle, 1995, Second-order analysis of space–time clustering, Statistical Methods in Medical Research, 4, 124, 10.1177/096228029500400203 Grekousis, 2011, A fuzzy index for detecting spatiotemporal outliers, GeoInformatica, 16, 597, 10.1007/s10707-011-0145-4 Grubesic, 2008, Spatio-temporal interaction of urban crime, Journal of Quantitative Criminology, 24, 285, 10.1007/s10940-008-9047-5 Gustafsson, 2000, Space–time clustering of childhood lymphatic leukaemias and non-hodgkin’s lymphomas in sweden, European Journal of Epidemiology, 16, 1111, 10.1023/A:1010953713048 Hoebe, 2004, Space–time cluster analysis of invasive meningococcal disease, Emerging Infectious Diseases, 10, 1621, 10.3201/eid1009.030992 Jacquez, 1996, A k nearest neighbour test for space–time interaction, Statistics in Medicine, 15, 1935, 10.1002/(SICI)1097-0258(19960930)15:18<1935::AID-SIM406>3.0.CO;2-I Jacquez, 2007, In search of induction and latency periods: Space–time interaction accounting for residential mobility, risk factors and covariates, International Journal of Health Geographics, 6, 35, 10.1186/1476-072X-6-35 Johnson, 2010, A brief history of the analysis of crime concentration, European Journal of Applied Mathematics, 21, 349, 10.1017/S0956792510000082 Johnson, 2007, Space–time patterns of risk: A cross national assessment of residential burglary victimization, Journal of Quantitative Criminology, 23, 201, 10.1007/s10940-007-9025-3 Johnson, 2004, The stability of space–time clusters of burglary, British Journal of Criminology, 44, 55, 10.1093/bjc/44.1.55 Klauber, 1970, Space–time clustering of childhood leukemia in San Francisco, Cancer Research, 30, 1969 Knox, 1964, The detection of space–time interactions, Journal of the Royal Statistical Society: Series C (Applied Statistics), 13, 25 Knox, 2002, An epidemic pattern of murder, Journal of Public Health, 24, 34, 10.1093/pubmed/24.1.34 Kulldorff, 1998, Statistical methods for spatial epidemiology: Tests for randomness, 49 Kulldorff, 1998, Evaluating cluster alarms: A space–time scan statistic and brain cancer in Los Alamos, New Mexico, American Journal of Public Health, 88, 1377, 10.2105/AJPH.88.9.1377 Kulldorff, 1999, The Knox method and other tests for space–time interaction, Biometrics, 55, 544, 10.1111/j.0006-341X.1999.00544.x Lu, 2003, Assessing the cluster correspondence between paired point locations, Geographical Analysis, 35, 290, 10.1111/j.1538-4632.2003.tb01116.x Lu, 2008, Cross-scale analysis of cluster correspondence using different operational neighborhoods, Journal of Geographic Systems, 10, 241, 10.1007/s10109-008-0069-1 Malizia, N. & Mack, E. A. (2012). Enhancing the Jacquez k nearest neighbor test for space–time interaction. Statistics in Medicine, http://dx.doi.org/10.1002/sim.5348. Mantel, 1967, The detection of disease clustering and a generalized regression approach, Cancer Research, 27, 209 Marshall, 1991, A review of methods for the statistical analysis of spatial patterns of disease, Journal of the Royal Statistical Society: Series A (Statistics in Society), 154, 421, 10.2307/2983152 McNally, 2002, Space–time clustering analyses of childhood acute lymphoblastic leukaemia by immunophenotype, British Journal of Cancer, 87, 513, 10.1038/sj.bjc.6600498 McNally, 2008, Space–time clustering analyses of occurrence of cerebral palsy in Northern England for births 1991 to 2003, Annals of Epidemiology, 18, 108, 10.1016/j.annepidem.2007.07.104 McNally, 2005, Is there a common aetiology for certain childhood malignancies? Results of cross-space–time clustering analyses, European Journal of Cancer, 41, 2911, 10.1016/j.ejca.2005.04.051 Norström, 2000, A space–time cluster investigation of an outbreak of acute respiratory disease in Norwegian cattle herds, Preventive Veterinary Medicine, 47, 107, 10.1016/S0167-5877(00)00159-8 Petridou, 1996, Space–time clustering of childhood leukaemia in Greece: Evidence supporting a viral aetiology, British Journal of Cancer, 73, 1278, 10.1038/bjc.1996.245 Rey, 2010, PySAL: A Python library of spatial analytical methods, 175 Rogerson, 2001, Monitoring point patterns for the development of space–time clusters, Journal of the Royal Statistical Society: Series A (Statistics in Society), 164, 87, 10.1111/1467-985X.00188 Rogerson, 2009 Tango, 2010 Townsley, 2003, Infectious burglaries: A test of the near repeat hypothesis, British Journal of Criminology, 43, 615, 10.1093/bjc/azg615 Ward, 2000, Analysis of time–space clustering in veterinary epidemiology, Preventive Veterinary Medicine, 43, 225, 10.1016/S0167-5877(99)00111-7 Williams, 1984, Time–space clustering of disease, 167