Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Muundo wa Dawa wa Mchanganyiko× | Kipimo cha Log-Rank cha Kulinganisha Milia ya Uhai× | |
|---|---|---|
| Nyanja | Uchanganuzi wa Uhai | Uchanganuzi wa Uhai |
| Familia | Survival analysis | Survival analysis |
| Mwaka wa asili≠ | 1949 | 1966 |
| Mwanzilishi≠ | Boag, J. W. | Mantel, N. |
| Aina≠ | Parametric mixture survival model | Non-parametric hypothesis test |
| Chanzo asilia≠ | Boag, J. W. (1949). Maximum Likelihood Estimates of the Proportion of Patients Cured. Journal of the Royal Statistical Society B, 11(1), 15–53. link ↗ | Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170. link ↗ |
| Majina mbadala | cure fraction model, cure rate model, bounded cumulative hazard model, İyileşme Modeli (Mixture Cure Model) | Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi |
| Zinazohusiana | 2 | 2 |
| Muhtasari≠ | The mixture cure model, first proposed by Boag in 1949 for cancer survival data, is a parametric survival model that explicitly accounts for a fraction of subjects who will never experience the event of interest — the so-called cured or immune fraction. It is the appropriate tool whenever the Kaplan-Meier curve levels off into a long, stable plateau rather than continuing to decline, indicating that a proportion of subjects are permanently event-free. | The log-rank test, developed by Nathan Mantel in 1966, is a non-parametric hypothesis test that compares the overall survival experience of two or more groups throughout the entire follow-up period. It is the standard companion to Kaplan-Meier curves and determines whether observed differences between curves are statistically meaningful. |
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