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Fig 1.

Choropleth maps displaying the simulated counts of lung cancer at multiple aggregation levels for Queensland, Australia.

Note that the maps for each aggregation level have different colour scales to reflect how the average counts per area increases as aggregation occurs.

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Fig 1 Expand

Fig 2.

Choropleth maps displaying the observed SIR from the simulated lung cancer data at multiple aggregation levels for Queensland, Australia (grey regions have 0 cases).

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Fig 2 Expand

Table 1.

Population and number of lung cancer diagnoses by geographic levels of aggregation.

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Table 1 Expand

Fig 3.

Choropleth maps displaying the fitted SIR (without covariate model) from the simulated lung cancer data at multiple aggregation levels for Queensland, Australia.

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Fig 3 Expand

Fig 4.

Choropleth maps displaying the fitted SIR (with covariate model) from the simulated lung cancer data at multiple aggregation levels for Queensland, Australia.

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Fig 4 Expand

Table 2.

Moran’s I of observed counts and modelled residuals.

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Table 2 Expand

Table 3.

Posterior summary of simulated lung cancer BYM model without covariates.

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Table 3 Expand

Table 4.

Posterior summary of simulated lung cancer BYM model with covariates.

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Table 4 Expand

Fig 5.

Credible intervals of parameters for BYM model with covariate.

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Fig 6.

Credible intervals of parameters for BYM model without covariate.

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