Estimating crude cumulative incidences through multinomial logit regression on discrete cause-specific hazards

Federico Ambrogi, Elia Biganzoli, Patrizia Boracchi

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)2767-2779
Number of pages13
JournalComputational Statistics and Data Analysis
Volume53
Issue number7
DOIs
Publication statusPublished - May 15 2009

ASJC Scopus subject areas

  • Computational Mathematics
  • Computational Theory and Mathematics
  • Statistics and Probability
  • Applied Mathematics

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