Table 5.

Variance and ICC for hospital-level random effects from multilevel logistic regression, all public and private hospitals in New South Wales, Australia (n=313)

		Hypertension (N=15 279)	Diabetes (N=4794)	Heart disease (N=8307)	Stroke (N=2480)	Smoking (N=2099)	Obesity (N=8162)
Hospital-level variance (SE)*
Model 0	Patient factors	0.80 (0.10)	0.27 (0.06)	0.91 (0.12)	0.38 (0.10)	0.35 (0.09)	0.68 (0.14)
Model 1	Model 0+hospital type (public/private)	0.65 (0.08)	0.27 (0.06)	0.71 (0.10)	0.16 (0.06)	0.35 (0.09)	0.69 (0.14)
Model 2	Model 0+hospital remoteness	0.77 (0.09)	0.25 (0.05)	0.92 (0.12)	0.37 (0.10)	0.33 (0.08)	0.68 (0.14)
Model 3	Model 0+hospital depth of coding	0.46 (0.06)	0.20 (0.05)	0.56 (0.08)	0.26 (0.08)	0.29 (0.08)	0.68 (0.14)
Model 4	Model 0+hospital peer group	0.72 (0.09)	0.21 (0.05)	0.75 (0.10)	0.34 (0.09)	0.31 (0.08)	0.67 (0.14)
(ICC (%)†		19.5	7.6	21.6	10.4	9.6	17.1
(MOR†		2.34	1.64	2.48	1.80	1.76	2.19

*Patient-level variance in a logistic regression is set at π²/3=3.29.³¹

†ICC and MOR calculated from model 0 (ICC=hospital-level variance divided by total variance (hospital-level+patient-level); MOR is calculated as ).³⁰

ICC, intraclass correlation coefficient; MOR, median OR; N, number of patients who self-reported condition.