Premium
Introduction to Survival Analysis
Author(s) -
Sainani Kristin L.
Publication year - 2016
Publication title -
pmandr
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 66
eISSN - 1934-1563
pISSN - 1934-1482
DOI - 10.1016/j.pmrj.2016.04.003
Subject(s) - censoring (clinical trials) , survival analysis , medicine , event (particle physics) , statistics , accelerated failure time model , surgery , mathematics , physics , quantum mechanics
Survival analysis is a set of statistical tools for analyzing time-to-event outcomes. Time-to-event variables record both whether participants had a binary outcome (eg, died/survived) and when events occurred, thus allowing researchers to calculate rates rather than just proportions. By focusing on rates, survival analysis methods (1) increase statistical power, (2) handle unequal followup times, and (3) permit the use of time-changing predictor variables. When planning cohort studies or randomized trials, researchers should consider collecting data on the timing of events to make survival analysis possible. This article reviews common statistical tests and graphics from the survival analysis toolkit.