Table 2 |
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Power of selected statistics for detecting data with local and global cluster types. |
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|
Global clustering methods |
Local cluster detection methods |
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|
|
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|
Tango_PDM |
Tango_ADJ |
Moran's I ADJ |
I*pop_ PD (λ = 5%) |
I*pop_ PD (λ = 50%) |
I*pop_ ADJ |
Local Moran's I |
SaTScana |
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|
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Local clusters relative risk = 4 sample size = 30,000 |
Two adjacent neighbors (Manassas City VA) |
0.107 |
0.127 |
0.024 |
.079 |
0.056 |
0.060 |
+ |
0.973 |
|
Six adjacent neighbors (Jackson County KS) |
0.089 |
0.124 |
0.027 |
.087 |
0.042 |
0.047 |
+ |
0.962 |
|
|
Ten adjacent neighbors (Fulton County GA) |
0.081 |
0.125 |
0.030 |
.079 |
0.043 |
0.055 |
+ |
0.979 |
|
|
|
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Global clustering relative risk = 1.5 sample size = 5.000 |
Linear |
0.997 |
0.285 |
0.232 |
.884 |
0.996 |
0.119 |
+ |
0.737 |
|
Exp |
0.998 |
0.291 |
0.235 |
.886 |
0.997 |
0.129 |
+ |
0.781 |
|
|
|
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a for global clustering evaluation, we used 50% of total population as the maximum search window. With the outlier detection, we use 5% of the total population as the maximum search window in SaTScan-E. + Power calculations are not available for Local Moran's I due to the fact that a statistics is produced for each geographic unit in the study. It is difficult to define power in the presence of multiple comparisons. |
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|
Jackson et al. International Journal of Health Geographics 2009 8:55 doi:10.1186/1476-072X-8-55 |
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