Nonparametric estimation in an "illness-death" model when all transition times are interval censored

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We develop nonparametric maximum likelihood estimation for the parameters of an irreversible Markov chain on states {0,1,2} from the observations with interval censored times of 0 → 1, 0 → 2 and 1 → 2 transitions. The distinguishing aspect of the data is that, in addition to all transition times being interval censored, the times of two events (0 → 1 and 1 → 2 transitions) can be censored into the same interval. This development was motivated by a common data structure in oral health research, here specifically illustrated by the data from a prospective cohort study on the longevity of dental veneers. Using the self-consistency algorithm we obtain the maximum likelihood estimators of the cumulative incidences of the times to events 1 and 2 and of the intensity of the 1 → 2 transition. This work generalizes previous results on the estimation in an "illness-death" model from interval censored observations.
Original languageEnglish
JournalBiometrical journal. Biometrische Zeitschrift
Volume55
Issue number6
Pages (from-to)823-43
Number of pages21
DOIs
Publication statusPublished - Nov 2013

    Research areas

  • Dental data, Interval censored "illness-death" model, Nonparametric maximum likelihood estimation, Randomized cohort study, Self-consistency equations

ID: 86128576