ENBIS-18 in Nancy

2 – 25 September 2018; Ecoles des Mines, Nancy (France) Abstract submission: 20 December 2017 – 4 June 2018

Effect of Several Failure Imputation Methods in Estimating the Survival Function under Interval Censoring

4 September 2018, 14:30 – 14:50

Abstract

Submitted by
Carlos M. Lopera-Gómez
Authors
Mario C. Jaramillo-Elorza (Universidad Nacional de Colombia), Carlos M. Lopera-Gómez (Universidad Nacional de Colombia)
Abstract
Most survival analyzes are based on exact failure times and right censored observations, using widely used statistical methods such as the Kaplan-Meier (KM) method. In medical studies the failure times (e.g. disease or relapse) are observed in the visits that pacients do to medical centers and this situation induces that the interval censoring arises. When interval censoring is present in data, it is necessary to use the Turnbull's method to estimate the survival function, however in practice the imputation of the failure time in this type of censoring is often done using the midpoint of the interval, the right end of the interval or a random point generated within the interval using the uniform distribution. This work through simulation studies the effect of the three types of imputation on the estimation of the survival curve compared to the Turnbull's method. Different simulation scenarios were analyzed based on sample size and time between visits. In all simulation scenarios, the functions estimated using data imputation differ significantly from the true survival function S(t).
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