Skip to main content

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

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

 

Coef

SE

CI (lower)

CI (higher)

  

Women

      

 Original dataa

      

  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 dataa

  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

  1. aRow normalised