Table 5.
Concordance rates between different clustering techniques and between indexes
| HC (5) a vs. quintiles b | HC (3) a vs. tiertiles b | HC (3) a vs. optimal thresholds b | Optimal thresholds vs. tiertiles b |
Carstairs |
Townsend |
|||
|---|---|---|---|---|---|---|---|---|
| HC (5) a vs. quintiles b | Optimal thresholds vs. tiertiles b | HC (5) a vs. quintiles b | Optimal thresholds vs. tiertiles b | |||||
| Lille Métropole |
41% |
78% |
98% |
79% |
38% |
70% |
42% |
78% |
| Grand Lyon |
48% |
74% |
93% |
78% |
47% |
77% |
40% |
75% |
| Marseille urban unit |
48% |
69% |
97% |
67% |
51% |
67% |
50% |
69% |
| Global | 63% | 71% | 97% | 72% | 57% | 70% | 55% | 71% |
aHierarchical Clustering using Principal Components (in parenthesis, the number of categories chosen).
bConcordance rate (percent of census block groups categorized into the same class using the two different clustering schemes).