A bootstrapping approach for generating an inverse distance weight matrix when multiple observations have an identical location in large health surveys

Table 5 Sensitivity analysis—spatial probit model (health service use)

	Coef	SE	CI (lower)	CI (higher)
Women
Original data^a
splag	4.310	0.420	3.486	5.134
Wealth	− 0.030	0.011	− 0.052	− 0.008
Education	0.076	0.024	0.028	0.124
_cons	− 2.319	0.248	− 2.805	− 1.832

	Coef	SE	Boot CI (lower)	Boot CI (higher)	Coverage probability (%)	MSE
5000 simulation
Wealth	− 0.012	0.029	− 0.070	0.045	94.6	0.001
Education	0.068	0.065	− 0.060	0.195	97.0	0.004
10,000 simulation
Wealth	− 0.012	0.030	− 0.071	0.047	94.4	0.001
Education	0.066	0.065	− 0.061	0.193	96.8	0.004

	Coef	SE	CI (lower)	CI (higher)
Men
Original data^a
splag	5.419	0.291	4.848	5.990
Wealth	− 0.031	0.008	− 0.046	− 0.016
Education	0.053	0.017	0.020	0.086
_cons	− 3.050	0.187	− 3.417	− 2.683

	Coef	SE	Boot CI (lower)	Boot CI (higher)	Coverage probability (%)	MSE
5000 simulation
Wealth	− 0.032	0.033	− 0.097	0.032	96.2	0.001
Education	0.057	0.073	− 0.086	0.199	95.7	0.005
10,000 simulation
Wealth	− 0.032	0.033	− 0.096	0.032	96.3	0.001
Education	0.057	0.074	− 0.088	0.201	95.7	0.005

ISSN: 1476-072X