Survival Analysis: Introduction

TY - ENCYC

T1 - Survival Analysis

T2 - Introduction

AU - Keiding, Niels

AU - Andersen, Per K.

PY - 2015

Y1 - 2015

N2 - Survival analysis is the study of the distribution of time-to-event data, that is, the times from an initiating event to some terminal event. A distinguishing feature of survival data is the occurrence of right censoring, where the terminal event for some individuals is not observed; instead, it is only known that this event is at least later than a given point in time. This article presents a brief historical review and focuses on central statistical approaches: non- and semiparametric estimation (Kaplan-Meier, Cox regression) and hypothesis testing (log-rank). We also add brief comments on parametric models and list some important reference works.

AB - Survival analysis is the study of the distribution of time-to-event data, that is, the times from an initiating event to some terminal event. A distinguishing feature of survival data is the occurrence of right censoring, where the terminal event for some individuals is not observed; instead, it is only known that this event is at least later than a given point in time. This article presents a brief historical review and focuses on central statistical approaches: non- and semiparametric estimation (Kaplan-Meier, Cox regression) and hypothesis testing (log-rank). We also add brief comments on parametric models and list some important reference works.

KW - Aalen additive hazards model

KW - Accelerated failure time model

KW - Censored data

KW - Cox regression

KW - Expected survival

KW - Kaplan-Meier estimator

KW - Log-rank test

KW - Nelson-Aalen estimator

KW - Poisson regression

KW - Time-to-event data

U2 - 10.1016/B978-0-08-097086-8.42019-2

DO - 10.1016/B978-0-08-097086-8.42019-2

M3 - Encyclopedia chapter

AN - SCOPUS:85043443733

SN - 9780080970868

SP - 771

EP - 775

BT - International Encyclopedia of the Social & Behavioral Sciences

A2 - Wright, James D.

PB - Elsevier Science Inc.

ER -