Binomial Regression Models

Authored by: Randi Grøn , Thomas A. Gerds

Handbook of Survival Analysis

Print publication date:  July  2013
Online publication date:  April  2016

Print ISBN: 9781466555662
eBook ISBN: 9781466555679
Adobe ISBN:

10.1201/b16248-14

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Abstract

Binomial regression is an estimation technique used for predicting a binary event status at future time points. In survival analysis the outcome is the time between a well-defined time origin (or ) and the occurrence of an event. The key to using binomial regression for time-to-event outcome is the observation that at any time horizon after the time origin the event status is binary, taking the value 1 if the event has occurred, and 0 otherwise. Clearly, the event status at a single time horizon carries much less information than the time-to-event outcome. However, the time process {N e (t)= I{T t,ϵ} : t ∈ [0, )} represents the same information as (T, ϵ), where ϵ indicates the type of the event and T the event time. Indeed, there is a one-to-one correspondence between binomial regression models and (Doksum and Gasko, 1990) which holds also in more complex models for event history analysis (Jewell, 2005).

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