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Joint Models For Longitudinal And Time To Event Data

Author: Dimitris Rizopoulos
Publisher: CRC Press
ISBN: 1439872864
Size: 60.53 MB
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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. All illustrations put forward can be implemented in the R programming language via the freely available package JM written by the author. All the R code used in the book is available at: http://jmr.r-forge.r-project.org/

Disease Modelling And Public Health

Author:
Publisher: Elsevier
ISBN: 0444639691
Size: 60.87 MB
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Disease Modelling and Public Health, Part A, Volume 36 addresses new challenges in existing and emerging diseases with a variety of comprehensive chapters that cover Infectious Disease Modeling, Bayesian Disease Mapping for Public Health, Real time estimation of the case fatality ratio and risk factor of death, Alternative Sampling Designs for Time-To-Event Data with Applications to Biomarker Discovery in Alzheimer's Disease, Dynamic risk prediction for cardiovascular disease: An illustration using the ARIC Study, Theoretical advances in type 2 diabetes, Finite Mixture Models in Biostatistics, and Models of Individual and Collective Behavior for Public Health Epidemiology. As a two part volume, the series covers an extensive range of techniques in the field. It present a vital resource for statisticians who need to access a number of different methods for assessing epidemic spread in population, or in formulating public health policy. Presents a comprehensive, two-part volume written by leading subject experts Provides a unique breadth and depth of content coverage Addresses the most cutting-edge developments in the field Includes chapters on Ebola and the Zika virus; topics which have grown in prominence and scholarly output

Handbook Of Survival Analysis

Author: John P. Klein
Publisher: CRC Press
ISBN: 146655567X
Size: 18.20 MB
Format: PDF
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Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time. With chapters written by leading researchers in the field, the handbook focuses on advances in survival analysis techniques, covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers, the book provides: An introduction to various areas in survival analysis for graduate students and novices A reference to modern investigations into survival analysis for more established researchers A text or supplement for a second or advanced course in survival analysis A useful guide to statistical methods for analyzing survival data experiments for practicing statisticians

Dynamical Biostatistical Models

Author: Daniel Commenges
Publisher: CRC Press
ISBN: 1498729681
Size: 70.26 MB
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Dynamical Biostatistical Models presents statistical models and methods for the analysis of longitudinal data. The book focuses on models for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. Most of the advanced methods, such as multistate and joint models, can be applied using SAS or R software. The book describes advanced regression models that include the time dimension, such as mixed-effect models, survival models, multistate models, and joint models for repeated measures and time-to-event data. It also explores the possibility of unifying these models through a stochastic process point of view and introduces the dynamic approach to causal inference. Drawing on much of their own extensive research, the authors use three main examples throughout the text to illustrate epidemiological questions and methodological issues. Readers will see how each method is applied to real data and how to interpret the results.

Regression

Author: Ludwig Fahrmeir
Publisher: Springer-Verlag
ISBN: 3642018378
Size: 76.94 MB
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In dem Band beschreiben die Autoren erstmals klassische Regressionsansätze und moderne nicht- und semiparametrische Methoden in einer integrierten und anwendungsorientierten Form. Um Lesern die Analyse eigener Fragestellungen zu ermöglichen, demonstrieren sie die praktische Anwendung der Konzepte und Methoden anhand ausführlicher Fallstudien. Geeignet für Studierende der Statistik sowie für Wissenschaftler und Praktiker, zum Beispiel in den Wirtschafts- und Sozialwissenschaften, der Bioinformatik und -statistik, Ökonometrie und Epidemiologie.

Programmieren Mit R

Author: Uwe Ligges
Publisher: Springer-Verlag
ISBN: 3540799982
Size: 60.55 MB
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R ist eine objektorientierte und interpretierte Sprache und Programmierumgebung für Datenanalyse und Grafik. Ausführlich führt der Autor in die Grundlagen ein und vermittelt eingängig die Struktur der Sprache. So ermöglicht er Lesern den leichten Einstieg: eigene Methoden umsetzen, Objektklassen definieren und Pakete aus Funktionen und zugehöriger Dokumentation zusammenstellen. Detailliert beschreibt er die enormen Grafikfähigkeiten von R. Für alle, die R als flexibles Werkzeug zur Datenanalyse und -visualisierung einsetzen. In 2. Auflage mit vielen Verbesserungen und Neuerungen von R-2.3.x und weiteren von Lesern gewünschten Ergänzungen.