Linganisha mbinu

	Mfumo wa Kunusurika wa Parametrici Unyumbufu (Royston-Parmar)	Kipimo cha Log-Rank cha Kulinganisha Milia ya Uhai
Nyanja	Uchanganuzi wa Uhai	Uchanganuzi wa Uhai
Familia	Survival analysis	Survival analysis
Mwaka wa asili	2002	1966
Mwanzilishi	Royston, P. & Parmar, M.K.B.	Mantel, N.
Aina	Parametric survival regression model	Non-parametric hypothesis test
Chanzo asilia	Royston, P. & Parmar, M.K.B. (2002). Flexible Parametric Proportional-Hazards and Proportional-Odds Models for Censored Survival Data, with Application to Prognostic Modelling and Estimation of Treatment Effects. Statistics in Medicine, 21(15), 2175–2197.	Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170.
Majina mbadala	flexible parametric model, restricted cubic spline survival model, stpm2, Esnek Parametrik Survival Modeli (Royston-Parmar)	Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
Zinazohusiana	8	2
Muhtasari	The Royston-Parmar model, introduced by Royston and Parmar in 2002, is a modern parametric approach to survival analysis that replaces the rigid distributional assumptions of classical models with a restricted cubic spline fitted to the log-cumulative-hazard scale. It combines the interpretability of a fully parametric model with the flexibility to capture non-standard hazard shapes, and it supports proportional-hazards, accelerated failure-time, and proportional-odds link functions.	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.