A Review of Life Table Construction

Etikán, Ílker

doi:10.15406/bbij.2017.05.00132

Cited by 1 publication

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several statistics like the number of patients at risk, survival proportion, hazard proportion, median survival time, and the survival rate can also be computed. Two specific types of life tables used widely in the statistical analysis are the cohort life table or follow-up life table [ 7 ]. It summarizes the experiences of individuals over a pre-defined follow-up period (cohort or clinical trial) until the event occurred or the study period ends.…”

Section: Methodsmentioning

confidence: 99%

Survival analysis: A primer for the clinician scientists

Rai

Mishra

Ghoshal

2021

Indian J Gastroenterol

View full text Add to dashboard Cite

Survival analysis is a collection of statistical procedures employed on time-to-event data. The outcome variable of interest is time until an event occurs. Conventionally, it dealt with death as the event, but it can handle any event occurring in an individual like disease, relapse from remission, and recovery. Survival data describe the length of time from a time of origin to an endpoint of interest. By time, we mean years, months, weeks, or days from the beginning of being enrolled in the study. The major limitation of time-to-event data is the possibility of an event not occurring in all the subjects during a specific study period. In addition, some of the study subjects may leave the study prematurely. Such situations lead to what is called censored observations as complete information is not available for these subjects. Life table and Kaplan–Meier techniques are employed to obtain the descriptive measures of survival times. The main objectives of survival analysis include analysis of patterns of time-to-event data, evaluating reasons why data may be censored, comparing the survival curves, and assessing the relationship of explanatory variables to survival time. Survival analysis also offers different regression models that accommodate any number of covariates (categorical or continuous) and produces adjusted hazard ratios for individual factor.

show abstract

Section: Methodsmentioning

confidence: 99%