Table 5 Coefficients for linear regression models predicting total costs for patients who dissave
Mean (se) coefficient values | |||
|---|---|---|---|
Predictors | Tanzania N = 57 | Bangladesh N = 53 | Bangalore N = 332 |
Intercept | 3.043e + 05 (1.630e + 05) | 1.889e + 04 (8.133e + 03)* | 1.036e + 04 (2.977e + 03)*** |
Dissaving amount | 2.181e-01 (1.684e-01) | 6.779e-01 (6.212e-02)*** | 7.648e-01 (6.057e-02)*** |
Age | −7.726e + 01 (1.313e + 02) | −7.726e + 01 (1.313e + 02) | −7.041e + 01 (4.033e + 01) |
Female gender | 8.589e + 03 (4.410e + 03) | 8.589e + 03 (4.410e + 03) | 2.815e + 03 (1.126e + 03)* |
Hospitalisation | −3.896e + 05 (8.473e + 04)*** | −1.431e + 04 (6.368e + 03)* | 3.201e + 03 (1.140e + 03)** |
Rural location | 1.609e + 05 (7.900e + 04)* | −7.219e + 03 (7.410e + 03) | NA |
SES | −2.195e + 05 (1.251e + 05) | 1.056e + 04 (5.116e + 03)* | NA |
Low SES | NA | NA | −8.996e + 03 (2.431e + 03)*** |
Medium SES | NA | NA | −8.679e + 03 (2.382e + 03)*** |
Income | NA | NA | 5.759e-01 (2.089e-01)** |