Table 1 Simulation results for 100 dataset consist of 200 subjects each with true parameter value \(\beta _1=-0.5,\beta _2=0.01,\beta _3=0.02\) and \(\beta _1=-0.5,\beta _2=0.43,\beta _3=0.03\).
From: Competing risk multistate censored data modeling by propensity score matching method
Parameters | Mean | Bias | MSE | Mean | Bias | MSE |
|---|---|---|---|---|---|---|
| Â | Without propensity score method (\(\tau _{01}\)) | Without propensity score method (\(\tau _{02}\)) | ||||
\(\beta _1(x_1)\) | − 0.522 | − 0.022 | 0.209 | − 0.519 | − 0.019 | 0.059 |
\(\beta _2(x_2)\) | 0.014 | 0.004 | 0.002 | 0.015 | 0.025 | 0.003 |
\(\beta _3(x_3)\) | 0.017 | 0.002 | 0.002 | 0.014 | − 0.185 | 0.002 |
| Â | With propensity score method | With propensity score method | ||||
\(\beta _1(x_1)\) | − 0.504 | − 0.004 | 0.156 | − 0.510 | − 0.010 | 0.003 |
\(\beta _2(x_2)\) | 0.048 | 0.005 | 0.039 | 0.048 | 0.0054 | 0.018 |
\(\beta _3(x_3)\) | 0.031 | 0.001 | 0.002 | 0.025 | 0.005 | 0.001 |
