INTERVAL CENSORED SURVIVAL DATA: A GENERALIZED LINEAR MODELLING APPROACH

Statistics in MedicinePublished 15 February 1996

Paddy Farrington

DOI10.1002/(sici)1097-0258(19960215)15:3<283::aid-sim171>3.0.co;2-t

Source URL

Citations38

SJR quartileQ1

SJR score1.27

SNIP1.33

TL;DR

Three types of models are discussed: additive and multiplicative hazard models with piecewise constant baseline hazard, and a proportional hazards model with discrete baseline survivor function that may be fitted in the statistical package GLIM.

Abstract

A method is described for weak parametric modelling of arbitrarily interval censored survival data using generalized linear models. The method makes use of an associated Bernoulli model, with standard errors based on the observed information matrix. Three types of models are discussed: additive and multiplicative hazard models with piecewise constant baseline hazard, and a proportional hazards model with discrete baseline survivor function. These models may be fitted in the statistical package GLIM.

Keywords

Mathematics

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