Linganisha mbinu

	Uchanganuzi wa Jedwali la Maisha	Makadirio ya Idadi ya Watu kwa Njia ya Vikundi-Vijenzi	Kikokotozi cha Kuishi cha Kaplan-Meier
Nyanja	Demografia	Demografia	Uchanganuzi wa Uhai
Familia	Survival analysis	Process / pipeline	Survival analysis
Mwaka wa asili	1984	2001	1958
Mwanzilishi	Demographic/actuarial tradition; Chiang	Preston, Heuveline & Guillot	Kaplan, E. L. & Meier, P.
Aina	Age-structured mortality estimator	Demographic projection pipeline	Non-parametric survival estimator
Chanzo asilia	Chiang, C. L. (1984). The Life Table and Its Applications. Robert E. Krieger Publishing. ISBN: 978-0-89874-565-2	Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 978-1-557-86451-2	Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481.
Majina mbadala	Mortality Table, Actuarial Table, Survival Table, Yaşam Tablosu	Cohort-Component Method, Component Method of Population Projection, Age-Sex-Specific Population Projection, Kohort-Bileşen Projeksiyonu	product-limit estimator, km curve, kaplan-meier sağkalım analizi
Zinazohusiana	3	3	2
Muhtasari	A life table is a systematic, age-structured summary of the mortality experience of a population. It traces a hypothetical cohort of births — conventionally 100,000 — through successive age intervals, recording how many survive, how many die, and how many person-years are lived at each interval. The method was formalized in its modern probabilistic form by Chiang (1984), synthesizing centuries of actuarial and demographic practice into a rigorous statistical framework applicable to human and biological populations alike.	Cohort-Component Projection is the standard demographic method for forecasting future population size and age-sex structure by explicitly tracking births, deaths, and migration for each age-sex cohort across discrete time steps. Systematically formalized in the textbook literature by Preston, Heuveline, and Guillot (2001), the method builds on foundational actuarial and demographic work dating to the early twentieth century and remains the workhorse technique used by national statistical offices and international organizations worldwide.	The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups.