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USING MULTIPLE DECREMENT MODELS TO ESTIMATE RISK AND MORBIDITY FROM SPECIFIC AIDS ILLNESSES
Author(s) -
HOOVER DONALD R.,
PENG YUN,
SAAH ALFRED J.,
DETELS ROGER R.,
DAY ROGER S.,
PHAIR JOHN P.
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(19961115)15:21<2307::aid-sim450>3.0.co;2-i
Subject(s) - medicine , bootstrapping (finance) , incidence (geometry) , pneumonia , parametric statistics , cytomegalovirus , disease , estimation , human immunodeficiency virus (hiv) , statistics , immunology , viral disease , mathematics , econometrics , herpesviridae , geometry , management , economics
A simple non‐parametric approach is developed to simultaneously estimate net incidence and morbidity time from specific AIDS illnesses in populations at high risk for death from these illnesses and other causes. The disease–death process has four‐stages that can be recast as two sandwiching three‐state multiple decrement processes. Non‐parametric estimation of net incidence and morbidity time with error bounds are achieved from these sandwiching models through modification of methods from Aalen and Greenwood, and bootstrapping. An application to immunosuppressed HIV‐1 infected homosexual men reveals that cytomegalovirus disease, Kaposi's sarcoma and Pneumocystis pneumonia are likely to occur and cause significant morbidity time.