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Table 5 Performance comparison of alternative estimators: mean square standardized residual. 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

0.913

0.948

0.983

0.891

0.948

0.980

Population-weighted average

0.817

0.735

1.076

0.473

0.260

0.624

Global Empirical Bayes

1.524

1.974

0.973

0.494

0.284

0.315

Local Empirical Bayes

0.823

0.799

1.011

0.519

0.318

0.667

Poisson kriging (true γR(h))

0.929

0.986

1.151

2.324

1.705

1.447

Poisson kriging

0.901

1.436

1.197

2.365

0.947

2.066

CERVIX CANCER

      

Observed rates

1.224

1.188

1.050

1.299

1.247

1.096

Population-weighted average

1.229

0.542

1.156

0.441

0.257

0.540

Global Empirical Bayes

1.506

1.476

1.028

0.354

0.248

0.289

Local Empirical Bayes

1.154

0.679

1.101

0.638

0.407

0.663

Poisson kriging (true γR(h))

1.135

1.053

1.032

1.184

0.754

1.039

Poisson kriging

1.071

0.760

1.252

0.880

0.600

1.179