Preprint Article Version 1 This version is not peer-reviewed

Using a Counting Process Method to Impute Censored Follow-up Time Data

Version 1 : Received: 17 March 2018 / Approved: 19 March 2018 / Online: 19 March 2018 (07:42:49 CET)

A peer-reviewed article of this Preprint also exists.

Efird, J.T.; Jindal, C. Using a Counting Process Method to Impute Censored Follow-Up Time Data. Int. J. Environ. Res. Public Health 2018, 15, 690. Efird, J.T.; Jindal, C. Using a Counting Process Method to Impute Censored Follow-Up Time Data. Int. J. Environ. Res. Public Health 2018, 15, 690.

Journal reference: Int. J. Environ. Res. Public Health 2018, 15, 690
DOI: 10.3390/ijerph15040690

Abstract

Censoring occurs when complete follow-up time information is unavailable for patients enrolled in a clinical study. The process is considered to be informative (nonignorable) if the likelihood function for the censoring model cannot be partitioned into a set of response parameters that are independent of the censoring parameters. In such cases, estimated survival time probabilities may be biased, prompting the need for special statistical methods to remedy the situation. The problem is especially salient when censoring is skewed toward the early phase of a study. In this paper, we describe a method to impute censored follow-up times using a counting process method.

Subject Areas

counting process; censoring; Cox proportional-hazard regression; Kaplan-Meier; imputation; survival analysis

Readers' Comments and Ratings (0)

Leave a public comment
Send a private comment to the author(s)
Rate this article
Views 0
Downloads 0
Comments 0
Metrics 0
Leave a public comment

×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.