Table 4 Comparison of estimated time and conditional AIC between indiCAR and other methods when data are generated with spatial random effect parameter, \({\varvec{\lambda }}=0.75\)
From: Individual level covariate adjusted conditional autoregressive (indiCAR) model for disease mapping
Sample per group | Total sample | Time to convergence (s) | Conditional AIC | ||||||
|---|---|---|---|---|---|---|---|---|---|
indiCAR | glmer with random intercept | hlmer with random intercept | hlmer with CAR | indiCAR | glmer with random intercept | hlmer with random intercept | hlmer with CAR | ||
Data generated in 100 groups | |||||||||
 1:50 | 2517 | 0.48 | 2.34 | 0.39 | 2.10 | 1748.78 | 1883.67 | 1881.69 | 1881.81 |
 1:100 | 4688 | 3.30 | 3.40 | 0.38 | 6.75 | 2821.61 | 2899.41 | 2897.73 | 2897.83 |
 1:500 | 26,519 | 4.23 | 23.71 | 1.92 | 15.52 | 15,865.50 | 15,943.65 | 15,943.58 | 15,943.55 |
 1:1000 | 52,911 | 188.19 | 61.84 | 3.62 | Not feasible | 32,632.45 | 32,669.39 | 32,669.18 | Not feasible |
Data generated in 400 groups | |||||||||
 1:50 | 10,118 | 51.55 | 14.81 | 2.65 | 138.33 | 5935.14 | 6323.31 | 6309.56 | 6309.44 |
 1:100 | 20,652 | 36.74 | 25.53 | 4.20 | 434.66 | 12,476.61 | 12,893.85 | 12,889.04 | 12,889.13 |
 1:500 | 103,267 | 85.75 | 73.45 | 22.31 | Not feasible | 60,233.22 | 60,533.49 | 60,533.24 | Not feasible |
 1:1000 | 205,739 | 113.65 | 236.95 | 46.23 | Not feasible | 120,212.20 | 120,423.70 | 120,423.00 | Not feasible |