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JOINT MODELS OF LONGITUDINAL AND TIME-TO-EVENT DATA: WITH APPLICATIONS IN R - DIMITRIS RIZOPOULOS

PRECIO: GRATIS
FORMATO: PDF EPUB MOBI
FECHA DE LANZAMIENTO: 2012
TAMAÑO DEL ARCHIVO: 7,12
ISBN: 9781439872864
IDIOMA: ESPAÑOL
AUTORA/AUTOR: DIMITRIS RIZOPOULOS

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Descripción:

In longitudinal studies it is often of interest to investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest, e.g., prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R provides a full treatment of random effects joint models for longitudinal and time-to-event outcomes that can be utilized to analyze such data. The content is primarily explanatory, focusing on applications of joint modeling, but sufficient mathematical details are provided to facilitate understanding of the key features of these models.

...is Rizopoulos: Amazon.es: Tienda Kindle Amazon配送商品ならJoint Models for Longitudinal and Time-to-Event Data: With Applications in R (Chapman & Hall/CRC Biostatistics Series)が通常配送無料。更にAmazonならポイント還元本が多数。Rizopoulos, Dimitris作品ほか、お急ぎ便対象商品は当日お届けも可能。 Joint Models for Longitudinal and Time-to-Event Data: With Applications in R Chapman & Hall/CRC Biostatistics Series: Amazon ... Joint Modeling in R ... .es: Rizopoulos, Dimitris: Libros en idiomas extranjeros References Joint modeling sources Rizopoulos, D. (2012). Joint Models for Longitudinal and Time-to-Event Data, with Applications in R.Boca Raton: Chapman & Hall/CRC. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R (Chapman & Hall/CRC Biostatistics Series) [Rizopoulos, Dimitris] on Amazon.com. *FREE* shipping on qualifying offers. Joint Models for Longitudinal and Time-to-Event Data: ... Joint Models for Longitudinal and Time-to-Event Data: With ... ... .es: Rizopoulos, Dimitris: Libros en idiomas extranjeros References Joint modeling sources Rizopoulos, D. (2012). Joint Models for Longitudinal and Time-to-Event Data, with Applications in R.Boca Raton: Chapman & Hall/CRC. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R (Chapman & Hall/CRC Biostatistics Series) [Rizopoulos, Dimitris] on Amazon.com. *FREE* shipping on qualifying offers. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R (Chapman & Hall/CRC Biostatistics Series) Joint Models for Longitudinal and Time-to-Event Data: With Applications in R (Chapman & Hall/CRC Biostatistics Series Book 6) eBook: Rizopoulos, Dimitris: Amazon.ca: Kindle Store provide a brief overview of a joint model approach for longitudinal and time-to-event data, focusing on the survival process. Also, the predictive capacity of this model is studied and related computational aspects, including available software, are discussed. The main motivation behind this work relies on the application of the joint modelling to time-to-event(s) of particular interest (e.g., death, relapse) • Implicit outcomes missing data (e.g., dropout, intermittent missingness) random visit times Joint Models for Longitudinal and Survival Data: August 19-23, 2019, Rotterdam viii Stanford Libraries' official online search tool for books, media, journals, databases, government documents and more. 2. MODEL SPECIFICATION. We consider here a basic joint model for a continuous longitudinal outcome and a time‐to‐event outcome. More specifically, let y i (t) be the longitudinal measurement for the ith patient at time t.The longitudinal outcome y i (t) is modeled by a mixed effects submodel.The design vector for the fixed effects is denoted by x i (t) and...