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CHARACTERIZATION OF HIV INCUBATION DISTRIBUTIONS AND SOME COMPARATIVE STUDIES
Author(s) -
TAN WAIYUAN,
LEE SHO RONG,
TANG SI CHIN
Publication year - 1996
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/(sici)1097-0258(19960130)15:2<197::aid-sim147>3.0.co;2-7
Subject(s) - parametric statistics , parametric model , statistic , mathematics , monte carlo method , statistics , residual , logistic regression , covariate , computer science , algorithm
In this paper we use a general stochastic model to characterize the HIV incubation distributions. We generate some Monte Carlo data under different conditions and compare the fitting of HIV incubation distributions by some well known parametric models and some non‐parametric methods. The parametric models include most of those that have appeared in the literature. The non‐parametric methods include the Kaplan–Meier method, the EMS method, the spline approximation and the Bacchetti method. The comparison criteria are the chi‐square statistic, the residual sum of squares, the AIC and the BIC. We show that the non‐parametric methods, especially the EMS method, provide excellent fits in almost all cases; for the parametric models, the generalized log‐logistic distributions with three and with four parameters fit better than other parametric models.