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USE OF A LOG‐LINEAR MODEL TO COMPUTE THE EMPIRICAL SURVIVAL CURVE FROM INTERVAL‐CENSORED DATA, WITH APPLICATION TO DATA ON TESTS FOR HIV POSITIVITY
Author(s) -
Becker Niels G.,
Melbye Mads
Publication year - 1991
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1991.tb00420.x
Subject(s) - nonparametric statistics , interval (graph theory) , statistics , confidence interval , computation , survival analysis , mathematics , interval data , log linear model , maximum likelihood , human immunodeficiency virus (hiv) , linear model , computer science , algorithm , medicine , combinatorics , virology , data envelopment analysis
Summary We describe how a log‐linear model can be used to compute the nonparametric maximum likelihood estimate of the survival curve from interval‐censored data. This permits such computation to be performed with the aid of readily available statistical software such as GLIM or SAS. The method is illustrated with reference to data from a cohort of Danish homosexual men, each of whom was tested for HIV positivity on one or more of six possible follow‐up times.