Skip to main content

Table 7 Performance comparison of alternative estimators: spread of the model of uncertainty. Results obtained on average over 100 realizations generated under two different population size scenarios and 3 types of risk map (1 = observed, 2 = smooth, 3 = random). Poisson kriging was conducted with the semivariogram estimated from the underlying risk values (true γR(h)) or the simulated mortality rates. Bold numbers refer to best performances outside the ideal case where the true semivariogram of risk is known.

From: Geostatistical analysis of disease data: estimation of cancer mortality risk from empirical frequencies using Poisson kriging

Estimators

WF population

BF population

BREAST CANCER

Scenario 1

Scenario 2

Scenario 3

Scenario 1

Scenario 2

Scenario 3

Observed rates

5.147

5.002

4.784

22482

21577

20641

Population-weighted average

4.057

1.603

7.712

17.60

16.28

20.97

Global Empirical Bayes

2.438

1.681

2.372

31.74

30.42

27.65

Local Empirical Bayes

2.050

1.143

2.422

16.98

16.53

18.88

Poisson kriging (true γR(h))

0.940

0.603

2.076

2.456

1.890

6.621

Poisson kriging

1.042

0.470

2.074

8.775

6.663

5.987

CERVIX CANCER

      

Observed rates

0.586

0.608

0.684

2359

2372

2625

Population-weighted average

0.494

0.242

0.883

2.870

2.631

3.233

Global Empirical Bayes

0.293

0.259

0.317

4.242

4.327

4.148

Local Empirical Bayes

0.229

0.170

0.307

2.843

2.722

3.130

Poisson kriging (true γR(h))

0.155

0.043

0.307

0.763

0.711

1.201

Poisson kriging

0.169

0.069

0.269

1.552

1.825

1.529