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Survival analysis

Survival analysis is a branch of statistics for analyzing the expected duration of time until one event occurs, such as death in biological organisms and failure in mechanical systems. This topic is called reliability theory, reliability analysis or reliability engineering in engineering, duration analysis or duration modelling in economics, and event…

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Overview

Introduction to survival analysis

General formulation

Censoring

Fitting parameters to data

Non-parametric estimation

Discrete-time survival models

Distributional Regression

Goodness of fit

Cure model

Distributions used in survival analysis

Applications

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Map overview Semantic statistics

Survival analysis

Nodes93
Edges92
Triples50
Avg. degree1.98
Density0.021505
Components1

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Survival analysis

Top relations

see also · 19
Survival analysis → Accelerated, Analysis, Approach, Class, Condition, Curve, Deaths, Frequency, Hypothesis, Medical, Meier, Method, Non-parametric, Parametric, Predicted, Probability, Rate, Statistical, Sub-discipline
related to External links · 17
Survival analysis → Analysis, Archived, Dr, Engineering Statistics Handbook, Mayo Clinic, NAG Fortran Library, NIST/SEMATEK, Package, Python, RLifelines, SOCR, Statistics' Textbook PageSurvival Analysis, Survival, Survival/Failure Time Analysis, Terry, Therneau, Therneau's
related to Censoring · 4
Survival analysis → Censoring, If, Right, We
related to Introduction to survival analysis · 3
Survival analysis → Meier, Survival, To
is a · 1
Survival analysis → branch of statistics for analyzing the expected duration of time until one event occurs

Important terminology Word statistics

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Important terminology

survival time data event function displaystyle hazard analysis models death example cox model failure subjects probability may censoring lifetime using

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Survival analysisis abranch of statistics for analyzing the expected duration of time until one event occurs0.90text
gene expressioninstance ofThe log-rank test and KM curves don't work easily with quantitative predictors0.80text
white blood countinstance ofThe log-rank test and KM curves don't work easily with quantitative predictors0.80text
or ageinstance ofThe log-rank test and KM curves don't work easily with quantitative predictors0.80text
imagesinstance ofDeep learning approaches have shown superior performance especially on complex input data modalities0.80text
clinical time-seriesinstance ofDeep learning approaches have shown superior performance especially on complex input data modalities0.80text
termination of study before all recruited subjects have shown the event of interest or the subject has left the study prior to experiencing an eventinstance ofCensoringCensoring is a form of missing data problem in which time to event is not observed for reasons0.80text
Survival analysisrelated to CensoringCensoring0.60section
Survival analysisrelated to CensoringIf0.60section
Survival analysisrelated to CensoringRight0.60section
Survival analysisrelated to CensoringWe0.60section
Survival analysisrelated to External linksTherneau0.60section

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