Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values

Research output: Book/Report › Book › Research › peer-review

Standard

Models for Multi-State Survival Data : Rates, Risks, and Pseudo-Values. / Andersen, Per Kragh; Ravn, Henrik; Furberg, Julie Kjærulff (Illustrator).

CRC Press, 2024. 292 p.

Research output: Book/Report › Book › Research › peer-review

Harvard

Andersen, PK, Ravn, H & Furberg, JK 2024, Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values. CRC Press. https://doi.org/10.1201/9780429029684

APA

Andersen, P. K., Ravn, H., & Furberg, J. K. (2024). Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values. CRC Press. https://doi.org/10.1201/9780429029684

Vancouver

Andersen PK, Ravn H, Furberg JK. Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values. CRC Press, 2024. 292 p. https://doi.org/10.1201/9780429029684

Author

Andersen, Per Kragh ; Ravn, Henrik ; Furberg, Julie Kjærulff. / Models for Multi-State Survival Data : Rates, Risks, and Pseudo-Values. CRC Press, 2024. 292 p.

Bibtex

@book{c43adffeddef4b2391dc77d335b06151,
title = "Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values",
abstract = "Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time. They find application particularly in biostatistics, medicine, and public health. The book includes mathematical detail which can be skipped by readers more interested in the practical examples. It is aimed at biostatisticians and at readers with an interest in the topic having a more applied background, such as epidemiology. This book builds on several courses the authors have taught on the subject. Key Features: • Intensity-based and marginal models • Survival data, competing risks, illness-death models, recurrent events • Includes a full chapter on pseudo-values • Intuitive introductions and mathematical details • Practical examples of event history data • Exercises Software code in R and SAS and the data used in the book can be found on the book{\textquoteright}s webpage.",
author = "Andersen, {Per Kragh} and Henrik Ravn and Furberg, {Julie Kj{\ae}rulff}",
note = "Publisher Copyright: {\textcopyright} 2024 Taylor & Francis Group, LLC.",
year = "2024",
doi = "10.1201/9780429029684",
language = "English",
isbn = "978-0-367-14002-1",
publisher = "CRC Press",

}

RIS

TY - BOOK

T1 - Models for Multi-State Survival Data

T2 - Rates, Risks, and Pseudo-Values

AU - Andersen, Per Kragh

AU - Ravn, Henrik

A2 - Furberg, Julie Kjærulff

N1 - Publisher Copyright: © 2024 Taylor & Francis Group, LLC.

PY - 2024

Y1 - 2024

N2 - Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time. They find application particularly in biostatistics, medicine, and public health. The book includes mathematical detail which can be skipped by readers more interested in the practical examples. It is aimed at biostatisticians and at readers with an interest in the topic having a more applied background, such as epidemiology. This book builds on several courses the authors have taught on the subject. Key Features: • Intensity-based and marginal models • Survival data, competing risks, illness-death models, recurrent events • Includes a full chapter on pseudo-values • Intuitive introductions and mathematical details • Practical examples of event history data • Exercises Software code in R and SAS and the data used in the book can be found on the book’s webpage.

AB - Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time. They find application particularly in biostatistics, medicine, and public health. The book includes mathematical detail which can be skipped by readers more interested in the practical examples. It is aimed at biostatisticians and at readers with an interest in the topic having a more applied background, such as epidemiology. This book builds on several courses the authors have taught on the subject. Key Features: • Intensity-based and marginal models • Survival data, competing risks, illness-death models, recurrent events • Includes a full chapter on pseudo-values • Intuitive introductions and mathematical details • Practical examples of event history data • Exercises Software code in R and SAS and the data used in the book can be found on the book’s webpage.

U2 - 10.1201/9780429029684

DO - 10.1201/9780429029684

M3 - Book

AN - SCOPUS:85169347018

SN - 978-0-367-14002-1

SN - 978-1-032-56869-0

BT - Models for Multi-State Survival Data

PB - CRC Press

ER -

ID: 390450119