Clustering in sparse data and an analysis of rhabdomyosarcoma incidence
Article first published online: 12 OCT 2006
Copyright © 1992 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 11, Issue 6, pages 761–768, 1992
How to Cite
Grimson, R. C., Aldrich, T. E. and Drane, J. W. (1992), Clustering in sparse data and an analysis of rhabdomyosarcoma incidence. Statist. Med., 11: 761–768. doi: 10.1002/sim.4780110607
- Issue published online: 12 OCT 2006
- Article first published online: 12 OCT 2006
- Manuscript Revised: OCT 1991
- Manuscript Received: NOV 1990
Time series of epidemiologic events often contain periods of atypically low or high frequency. Correspondingly, for quite rare diseases there occur instances of long vacuous durations interrupted noticeably by periods of some disease activity. A recent community-based observation of the incidence of rhabdomyosarcoma (RMS), and an investigation of it, yielded sparse data of this general description. We introduce a combinatorial test for patchy time series and apply it to the RMS data. We comment on the prevalent practice of post hoc data analysis of alleged clusters, and on scale effects.