The Knox method and other tests for space-time interaction

Biometrics

Volumn 55, Issue 2, 1999, Pages 544-552

  Kulldorff, Martin ^a,b   Hjalmars, Ulf ^c  

^a NATIONAL CANCER INSTITUTE   (United States)

^b UNIVERSITY OF CONNECTICUT SCHOOL OF MEDICINE   (United States)

^c ÖSTERSUND HOSPITAL   (Sweden)

Author keywords

Bias; Epidemiology; Jaequez's test; Knox test; Mantel's test; Population shifts; Power; Space time clustering; Spatial statistics

Indexed keywords

GEOGRAPHICAL REGIONS; POPULATION STATISTICS;

BIAS; JAEQUEZ TEST; KNOX TEST; MANTEL TESTS; POPULATION GROWTH; POPULATION SHIFT; POWER; SPACE TIME CLUSTERING; SPACE-TIME INTERACTIONS; SPATIAL STATISTICS;

MONTE CARLO METHODS;

ARTICLE; BIOMETRY; EPIDEMIOLOGICAL DATA; GEOGRAPHY; HUMAN; MATHEMATICAL COMPUTING; POPULATION DYNAMICS; POPULATION GROWTH; POPULATION RESEARCH; STATISTICAL ANALYSIS;

EID: 0033004946     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.1999.00544.x     Document Type: Article

References (18)

1. Aldrich, T. E. and Drane, J. W. (1993). Cluster, Version 3.0, A Program for Identifying and Analyzing the Spatial and Temporal Structure of Chronic Disease Patterns. Washington, D.C.: Agency for Toxic Substances and Disease Registry.
2. Alexander, F. E. (1992). Space-time clustering of childhood acute lymphoblastic leukemia: Indirect evidence for a transmissible agent. British Journal of Cancer 65, 589-592.
3. Baker, R. D. (1996). Testing for space-time clusters of unknown size. Journal of Applied Statistics 23, 543-554.
4. Barton, D. E. and David, F. N. (1966). The random intersection of two graphs. In Research Papers in Statistics, Festschrift for J. Neyman, F. N. David (ed), 445-459. New York: Wiley.
5. Chen, R., Mantel, N., and Klingberg, M. A. (1984). A study of three techniques for time-space clustering in Hodgkin's disease. Statistics in Medicine 3, 173-184.
6. David, F. N. and Barton, D. E. (1966). Two space-time interaction tests for epidemicity. British Journal of Preventive Social Medicine 20, 44-48.
7. Diggle, P., Chetwynd, A. G., Häggkvist, R., and Morris, S. E. (1995). Second-order analysis of space-time clustering. Statistical Methods in Medical Research 4, 124-136.
8. Dwass, M. (1957). Modified randomization tests for nonparametric hypotheses. Annals of Mathematical Statistics 28, 181-187.
9. Gilman, E. A. and Knox, E. G. (1995). Childhood cancers: Space-time distribution in Britain. Journal of Epidemiology and Community Health 49, 158-163.
10. Jacquez, G. M. (1994). Stat!: Statistical Software for the Clustering of Health Events. Ann Arbor, Michigan: BioMedware.
11. Jacquez, G. M. (1996). A k nearest neighbor test for space-time interaction. Statistics in Medicine 15, 1935-1949.
12. Klauber, M. R. and Mustacchi, P. (1970). Space-time clustering of childhood leukemia in San Francisco. Cancer Research 30, 1969-1973.
13. Knox, G. (1964). The detection of space-time interactions. Applied Statistics 13, 25-29.
14. Kulldorff, M. (1998). Statistical methods for spatial epidemiology: Tests for randomness. In GIS and Health in Europe, A. Gatrell and M. Löytönen (eds). 49-62. London: Taylor and Francis.
15. Mantel, N. (1967). The detection of disease clustering and a generalized regression approach. Cancer Research 27, 209-220.
16. Petridou, E., Revinthi, K., Alexander, F. E., Haidas, S., Koliouskas, D., Kosmidis, H., Piperopoulou, F., Tzortzatou, F., and Trichopoulos, D. (1996). Space-time clustering of childhood leukemia in Greece: Evidence supporting a viral etiology. British Journal of Cancer 73, 1278-1283.
17. Pike, M. C. and Smith, P. G. (1968). Disease clustering: A generalization of Knox's approach to the detection of space-time interactions. Biometrics 24, 541-556.
18. Williams, G. W. (1984). Time-space clustering of disease. In Statistical Methods for Cancer Studies, R. G. Cornell (ed), 167-227. New York: Marcel Dekker.