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

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Nonparametric estimation in an "illness-death" model when all transition times are interval censored. / Frydman, Halina; Gerds, Thomas; Grøn, Randi; Keiding, Niels.

In: Biometrical journal. Biometrische Zeitschrift, Vol. 55, No. 6, 11.2013, p. 823-43.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Frydman, H, Gerds, T, Grøn, R & Keiding, N 2013, 'Nonparametric estimation in an "illness-death" model when all transition times are interval censored', Biometrical journal. Biometrische Zeitschrift, vol. 55, no. 6, pp. 823-43. https://doi.org/10.1002/bimj.201200139

APA

Frydman, H., Gerds, T., Grøn, R., & Keiding, N. (2013). Nonparametric estimation in an "illness-death" model when all transition times are interval censored. Biometrical journal. Biometrische Zeitschrift, 55(6), 823-43. https://doi.org/10.1002/bimj.201200139

Vancouver

Frydman H, Gerds T, Grøn R, Keiding N. Nonparametric estimation in an "illness-death" model when all transition times are interval censored. Biometrical journal. Biometrische Zeitschrift. 2013 Nov;55(6):823-43. https://doi.org/10.1002/bimj.201200139

Author

Frydman, Halina ; Gerds, Thomas ; Grøn, Randi ; Keiding, Niels. / Nonparametric estimation in an "illness-death" model when all transition times are interval censored. In: Biometrical journal. Biometrische Zeitschrift. 2013 ; Vol. 55, No. 6. pp. 823-43.

Bibtex

@article{93072ef50be241eaad2bc6ebbd50b9af,
title = "Nonparametric estimation in an {"}illness-death{"} model when all transition times are interval censored",
abstract = "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.",
keywords = "Dental data, Interval censored {"}illness-death{"} model, Nonparametric maximum likelihood estimation, Randomized cohort study, Self-consistency equations",
author = "Halina Frydman and Thomas Gerds and Randi Gr{\o}n and Niels Keiding",
note = "{\textcopyright} 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.",
year = "2013",
month = nov,
doi = "10.1002/bimj.201200139",
language = "English",
volume = "55",
pages = "823--43",
journal = "Biometrical Journal",
issn = "0323-3847",
publisher = "Wiley - V C H Verlag GmbH & Co. KGaA",
number = "6",

}

RIS

TY - JOUR

T1 - Nonparametric estimation in an "illness-death" model when all transition times are interval censored

AU - Frydman, Halina

AU - Gerds, Thomas

AU - Grøn, Randi

AU - Keiding, Niels

N1 - © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PY - 2013/11

Y1 - 2013/11

N2 - 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.

AB - 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.

KW - Dental data

KW - Interval censored "illness-death" model

KW - Nonparametric maximum likelihood estimation

KW - Randomized cohort study

KW - Self-consistency equations

U2 - 10.1002/bimj.201200139

DO - 10.1002/bimj.201200139

M3 - Journal article

C2 - 24038105

VL - 55

SP - 823

EP - 843

JO - Biometrical Journal

JF - Biometrical Journal

SN - 0323-3847

IS - 6

ER -

ID: 86128576