Võrdle meetodeid

	Landmark-analüüs tingimuslikuks elulemuseks ja dünaamiliseks ennustamiseks	Ühismudel pikisuunaliste ja sündmuseni kuluvate aegade andmestikule	Nelson-Aaleni kumulatiivse hasardfunktsiooni estimaator
Valdkond	Elukestusanalüüs	Elukestusanalüüs	Elukestusanalüüs
Perekond	Survival analysis	Survival analysis	Survival analysis
Tekkeaasta	1983	2004	1972
Looja	Anderson, J. R., Cain, K. C. & Gelber, R. D.	Tsiatis, A.A. & Davidian, M.; Rizopoulos, D.	Wayne Nelson & Odd Aalen
Tüüp	Conditional survival estimator	Semiparametric regression model	Non-parametric cumulative hazard estimator
Algallikas	Anderson, J. R., Cain, K. C. & Gelber, R. D. (1983). Analysis of Survival by Tumor Response. Journal of Clinical Oncology, 1(11), 710–719.	Rizopoulos, D. (2012). Joint Models for Longitudinal and Time-to-Event Data. CRC Press.	Nelson, W. (1972). Theory and applications of hazard plotting for censored failure data. Technometrics, 14(4), 945–966.
Rööpnimetused	landmark method, dynamic prediction, conditional survival estimation, Landmark Analizi (Dinamik Tahmin)	joint model, shared random effects model, longitudinal-survival joint model, Joint Model (Boylamsal + Sağkalım Birleşik Model)	Nelson-Aalen cumulative hazard, Aalen estimator, empirical cumulative hazard, Nelson-Aalen kümülatif hazard tahmincisi
Seotud	3	5	5
Kokkuvõte	Landmark analysis, introduced by Anderson, Cain, and Gelber in 1983, estimates conditional survival probabilities for subjects who are still at risk at a pre-specified point in time — the landmark — rather than at study entry. It was developed explicitly to avoid immortal time bias that arises when subjects are grouped by an event (such as a treatment change or biomarker result) that can only occur if they remain event-free long enough to experience it.	The joint model for longitudinal and time-to-event data, formalised by Tsiatis and Davidian in 2004 and extended comprehensively by Rizopoulos in 2012, simultaneously estimates a mixed-effects model for repeatedly measured biomarkers and a survival model for the time to an event, linking the two processes through shared random effects. It resolves two major problems that simpler approaches cannot handle: informative dropout from longitudinal studies and the endogeneity of time-varying biomarkers used as covariates in a Cox model.	The Nelson-Aalen estimator is a non-parametric estimator of the cumulative hazard function from right-censored time-to-event data. Developed by Wayne Nelson for reliability hazard plotting in 1972 and placed on a rigorous counting-process foundation by Odd Aalen in 1978, it accumulates the ratio of observed events to the number at risk at each event time, providing the natural hazard-scale companion to the Kaplan-Meier survival curve.