| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Song, Changhong Kulldorff, Martin |
| Abstract | Background Tango's maximized excess events test (MEET) has been shown to have very good statistical power in detecting global disease clustering. A nice feature of this test is that it considers a range of spatial scale parameters, adjusting for the multiple testing. This means that it has good power to detect a wide range of clustering processes. The test depends on the functional form of a weight function, and it is unknown how sensitive the test is to the choice of this weight function and what function provides optimal power for different clustering processes. In this study, we evaluate the performance of the test for a wide range of weight functions. Results The power varies greatly with different choice of weight. Tango's original choice for the weight function works very well. There are also other weight functions that provide good power. Conclusion We recommend the use of Tango's MEET to test global disease clustering, either with the original weight or one of the alternate weights that have good power. |
| Related Links | https://ij-healthgeographics.biomedcentral.com/counter/pdf/10.1186/1476-072X-4-32.pdf |
| Ending Page | 7 |
| Page Count | 7 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| DOI | 10.1186/1476-072X-4-32 |
| Journal | International Journal of Health Geographics |
| Issue Number | 1 |
| Volume Number | 4 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2005-12-15 |
| Access Restriction | Open |
| Subject Keyword | Public Health Health Informatics Human Geography Epidemiology Health Promotion and Disease Prevention Medical Geography Weight Function Cluster Model Hamiltonian Cycle Benchmark Data D_EET |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science Public Health, Environmental and Occupational Health Business, Management and Accounting |
| Journal Impact Factor | 3/2023 |
| 5-Year Journal Impact Factor | 4.1/2023 |
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