From: A systematic comparison of recurrent event models for application to composite endpoints
Scenario | \(\lambda _{0}^{MI}(t,t_{prev})\) | \(\lambda _{0}^{D}(t,t_{prev})\) | exp(βMI(t prev )) | exp(βD(t prev )) |
1a | 0.25 | 0.25 | 0.5 | 0.5 |
1b | 0.25 | 0.25 | 0.5 | 0.7 |
1c | 0.25 | 0.25 | 0.7 | 0.5 |
1d | 0.25 | 0.25 | 0.7 | 1.5 |
1e | 0.25 | 0.25 | 1.5 | 0.7 |
2a | \(0.25\cdot 1/\sqrt {t_{prev}}\) | \(0.25\cdot 1/\sqrt {t_{prev}}\) | 0.5 | 0.5 |
2b | \(0.25\cdot 1/\sqrt {t_{prev}}\) | \(0.25\cdot 1/\sqrt {t_{prev}}\) | 0.5 | 0.7 |
2c | \(0.25\cdot 1/\sqrt {t_{prev}}\) | \(0.25\cdot 1/\sqrt {t_{prev}}\) | 0.7 | 0.5 |
2d | \(0.25\cdot 1/\sqrt {t_{prev}}\) | \(0.25\cdot 1/\sqrt {t_{prev}}\) | 0.7 | 1.5 |
2e | \(0.25\cdot 1/\sqrt {t_{prev}}\) | \(0.25\cdot 1/\sqrt {t_{prev}}\) | 1.5 | 0.7 |
3a | t 0.3 | t 0.3 | 0.5 | 0.5 |
3b | t 0.3 | t 0.3 | 0.5 | 0.7 |
3c | t 0.3 | t 0.3 | 0.7 | 0.5 |
3d | t 0.3 | t 0.3 | 0.7 | 1.5 |
3e | t 0.3 | t 0.3 | 1.5 | 0.7 |
3f | 1.5·t0.3 | t 0.3 | 0.5 | 0.5 |
4a | 0.25 | 0.25 | 0.5 exp(0.05ln(0.5)·t prev ) | 0.5 exp(0.05ln(0.5)·t prev ) |
4b | 0.25 | 0.25 | 0.5 exp(0.05ln(0.5)·t prev ) | 0.7 exp(0.05ln(0.7)·t prev ) |
4c | 0.25 | 0.25 | 0.7 exp(0.05ln(0.7)·t prev ) | 0.5 exp(0.05ln(0.5)·t prev ) |
4d | 0.25 | 0.25 | 0.7 exp(0.05ln(0.7)·t prev ) | 1.5 exp(0.05ln(1.5)·t prev ) |
4e | 0.25 | 0.25 | 1.5 exp(0.05ln(1.5)·t prev ) | 0.7 exp(0.05ln(0.7)·t prev ) |
5a | 0.25 | 0.25 | 0.5 exp(−0.05ln(0.5)·t prev ) | 0.5 exp(−0.05ln(0.5)·t prev ) |
5b | 0.25 | 0.25 | 0.5 exp(−0.05ln(0.5)·t prev ) | 0.7 exp(−0.05ln(0.7)·t prev ) |
5c | 0.25 | 0.25 | 0.7 exp(−0.05ln(0.7)·t prev ) | 0.5 exp(−0.05ln(0.5)·t prev ) |
5d | 0.25 | 0.25 | 0.7 exp(−0.05ln(0.7)·t prev ) | 1.5 exp(−0.05ln(1.5)·t prev ) |
5e | 0.25 | 0.25 | 1.5 exp(−0.05ln(1.5)·t prev ) | 0.7 exp(−0.05ln(0.7)·t prev ) |
5f | 0.25 | 0.25 | 0.5 exp(−0.5ln(0.5)·t prev ) | 0.5 exp(−0.5ln(0.5)·t prev ) |