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Table 4 Global clustering test results with different adjustments.

From: Evaluation of the performance of tests for spatial randomness on prostate cancer data

Data/Model Cuzick-Edwards k-NN Moran's I Tango's MEET
  k = 1%   k= 1%    
  Test Statistic p-value Test Statistic p-value Test Statistic p-value
Later Stage       
1:Unadjusted data 173544 0.001 0.779 0.001 <10-15 0.0001
2:Individual-level adjustments; no area-level random effects 170735 0.001 0.672 0.001 3.89 × 10-15 0.0001
3:Individual-level adjustments; area-level random effects 170899 0.001 0.675 0.001 3.44 × 10-15 0.0001
4:Individual- and area-level adjustments; no area-level random effects 168227 0.001 0.483 0.001 2.18 × 10-08 0.0001
5:Individual- and area-level adjustments; area-level random effects 168684 0.001 0.489 0.001 7.17 × 10-10 0.0001
Higher Grade       
1:Unadjusted data 197019 0.001 0.478 0.001 1.36 × 10-13 0.0001
2:Individual-level adjustments; no area-level random effects 195707 0.001 0.350 0.001 4.11 × 10-08 0.0001
3:Individual-level adjustments; area-level random effects 195727 0.001 0.351 0.001 4.31 × 10-08 0.0001
4:Individual- and area-level adjustments; no area-level random effects 195085 0.001 0.355 0.001 2.18 × 10-08 0.0001
5:Individual- and area-level adjustments; area-level random effects 197598 0.001 0.701 0.001 <10-15 0.0001
  1. Higher values of the test statistic indicate more clustering for Cuzick-Edward's k-NN and Moran's I and less clustering for Tango's MEET. Test statistics can only be compared between models, not between the three methods.