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Table 6 Comparison of individual covariate adjusted conditional autoregressive model (indiCAR) with the Leroux et al. [7] method based on age-sex adjustments

From: Individual level covariate adjusted conditional autoregressive (indiCAR) model for disease mapping

Regression coefficients

indiCAR

Leroux et al.

Estimates

SE

Estimates

SE

Intercept

−2.781

0.110

–

–

Age group (years)

 20–30

0.124

0.056

–

–

 30–39

0.208

0.042

–

–

 40–49

Ref.

   

 50–59

−0.119

0.031

–

–

 60–69

−0.287

0.031

–

–

 70–79

−0.712

0.033

–

–

 80+

−1.586

0.045

–

–

Sex

 Female

Ref.

   

 Male

−0.082

0.020

–

–

Year of diagnosis

 2001

Ref.

   

 2002

0.018

0.038

–

–

 2003

0.083

0.038

–

–

 2004

0.021

0.038

–

–

 2005

0.096

0.037

–

–

 2006

0.036

0.038

–

–

 2007

0.026

0.038

–

–

 2008

−0.001

0.038

–

–

 2009

−0.315

0.042

–

–

ARIA

 Major cities

Ref.

   

 Inner regional Australia

−0.023

0.047

–

–

 Outer regional Australia

−0.147

0.068

–

–

 Remote/very remote Australia

−0.231

0.163

–

–

Cancer type

 Breast cancer

Ref.

–

–

–

 Lung cancer

0.253

0.038

–

–

 Colon and rectum cancer

−0.434

0.040

–

–

 Haematological malignancy

1.572

0.029

–

–

 Other cancer

−0.942

0.031

–

–

No. of major comorbidities

 0

Ref.

–

–

 

 1

0.413

0.026

–

–

 2

0.670

0.026

–

–

 3

0.609

0.036

–

–

 4+

0.605

0.035

–

–

SEIFA

 Most disadvantaged

Ref.

   

 2

−0.083

0.044

−0.075

0.042

 3

−0.071

0.041

−0.068

0.038

 4

−0.125

0.047

−0.121

0.044

 Least disadvantaged

−0.131

0.056

−0.129

0.052

Variance parameter

 σ

0.204

0.022

0.210

0.022

 λ

0.992

0.012

0.989

0.015