Estimating crude cumulative incidences through multinomial logit regression on discrete cause-specific hazards
Articolo
Data di Pubblicazione:
2009
Citazione:
Estimating crude cumulative incidences through multinomial logit regression on discrete cause-specific hazards / F. Ambrogi, E. Biganzoli, P. Boracchi. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - 53:7(2009 May 15), pp. 2767-2779. [10.1016/j.csda.2009.01.001]
Abstract:
In the presence of competing risks, the estimation of crude cumulative incidence, i.e. the probability of a specific failure as time progresses, has received much attention in the methodological literature. It is possible to estimate crude cumulative incidence starting from models defined on cause-specific hazards or to adopt regression strategies modeling directly the quantity of interest. A generalized linear model based on discrete cause-specific hazard is used to obtain the crude cumulative incidence and its asymptotic variance. The model allows inference both on cause-specific hazard and on crude cumulative incidence in the presence of time dependent effects. Standard software can be used to compute all quantities of interest. A trial of chemoprevention of leukoplakia is considered for illustrative purposes, where different patterns of risk are suspected for the different causes of treatment failure.
Tipologia IRIS:
01 - Articolo su periodico
Elenco autori:
F. Ambrogi, E. Biganzoli, P. Boracchi
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