Table 2

Parameter estimates for the auto-logistic regression models fit using the foundation doctor data

Model		Parameter estimate	SE (Hessian derived)	Lower CI (including Monte Carlo Standard Error (MCSE))	Upper CI (including MCSE)	χ²	P value
Auto-logistic model 1 (equation 2) Maximum Likelihood (ML): 107.835	(Intercept)	0.984	0.409	0.180	1.788	5.679	0.017
	(Number of neighbours)	−0.105	0.062	−0.227	0.017	2.862	0.091
	γ	0.965	0.365	0.248	1.682	7.051	0.008
Auto-logistic model 2 (equation 2) ML: 108.702	α(Intercept)	0.933	0.509	−0.064	1.930	3.362	0.067
	(1=Year 2)	−0.132	0.385	−0.886	0.622	0.118	0.732
	(1=West)	0.295	0.375	−0.440	1.030	0.618	0.432
	(1=female)	0.103	0.402	−0.685	0.891	0.066	0.798
	(Number of neighbours)	−0.100	0.066	−0.229	0.029	2.315	0.128
	γ	0.795	0.377	0.056	1.534	4.441	0.035