Developing the atlas of cancer in Queensland: methodological issues

Table 3 Sensitivity analyses for oesophageal cancer incidence among males

	Prior 1	Prior 2	Prior 3	Prior 4	Prior 5	Prior 6
Distribution of SIR
Mean	100.8	99.4	101.5	100.7	100.6	103.6
Standard deviation	10.2	30.8	16.3	14.5	13.5	23.2
Maximum	140.6	455.1	181.2	169.5	166.4	201.8
75% Quartile	107.2	113.1	111.7	110.2	109.4	109.8
Median	96.5	93.5	95.1	95.6	95.9	95.7
25% Quartile	93.3	78.7	89.4	89.9	90.7	90.2
Minimum	87.4	55.9	79.6	79.3	80.0	79.8
90% ratio¹	1.3	2.3	1.6	1.5	1.5	1.6
pD²	34.112	138.047	51.305	53.828	53.709	54.098
DIC³	1652.57	1660.32	1650.62	1648.51	1651.02	1650.71
Spatial fraction⁴	0.56	0.44	0.63	0.48	0.52	0.57
Percent SLAs with Geweke <0.01 for SIR	41.0%	1.9%	3.3%	9.4%	10.3%	10.5%

Notes:
1. The 90% ratio is calculated as the 95^th percentile divided by the 5^th percentile of the smoothed SIR estimates.
2. pD represents the effective number of parameters in the model. Larger values indicate less smoothing of estimates.
3. DIC = Deviance Information Criterion. Smaller values (of at least 5 below) indicate a better model fit.
4. The spatial fraction estimates the relative contribution of spatial and unstructured heterogeneity, and is calculated as: $Spatial fraction = \frac{θ_{m a r g i n a l}^{2}}{θ_{m a r g i n a l}^{2} + σ^{2}}$
where $θ_{m a r g i n a l}^{2}$ = marginal spatial variance, σ ²= marginal variability of the unstructured random effects between areas. A value close to 1 indicates the spatial heterogeneity dominates, whereas a value close to 0 indicates the unstructured heterogeneity dominates.

ISSN: 1476-072X