Modelling Survival Data in Medical Research, Third Edition (Chapman & Hall/CRC Texts in Statistical

Author by : David Collett
Languange Used : en
Release Date : 2015-05-04
Publisher by : CRC Press

ISBN :

Description : Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research.Well known for its nontechnical style, this third edition contains new chapters on frailty models and their applications, competing risks, non-proportional hazards, and dependent censo...

Author by : David Collett
Languange Used : en
Release Date : 2014-12-11
Publisher by : Chapman and Hall/CRC

ISBN :

Description : Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research. Well known for its nontechnical style, this third edition contains new chapters on frailty models and their applications, competing risks, non-proportional hazards, and dependent censoring. It also describes techniques for modelling the occurrence of multiple events and event history analysis. Earlier chapters are now expanded to include new material on a number of topics, including measures of predictive ability and flexible parametric models. Many new data sets and examples are included to illustrate how these techniques are used in modelling survival data. Bibliographic notes and suggestions for further reading are provided at the end of each chapter. Additional data sets to obtain a fuller appreciation of the methodology, or to be used as student exercises, are provided in the appendix. All data sets used in this book are also available in electronic format online. This book is an invaluable resource for statisticians in the pharmaceutical industry, professionals in medical research institutes, scientists and clinicians who are analyzing their own data, and students taking undergraduate or postgraduate courses in survival analysis....

Author by : D. Collett
Languange Used : en
Release Date : 1994
Publisher by : Chapman and Hall/CRC

ISBN :

Description : An introduction to modelling survival data in medical research. It demonstrates how widely available computer software can be used in survival analysis. It seeks to provide sufficient methodological development for the reader to understand assumptions upon which techniques are based, and to help the reader to adapt the methodology to deal with non-standard problems....

Author by : David Collett
Languange Used : en
Release Date : 2003-03-28
Publisher by : CRC Press

ISBN :

Description : Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in Medical Research has been thoroughly revised and updated to reflect the many developments and advances--particularly in software--made in the field over the last 10 years. Now, more than ever, it provides an outstanding text for upper-level and graduate courses in survival analysis, biostatistics, and time-to-event analysis.The treatment begins with an introduction to survival analysis and a description of four studies that lead to survival data. Subsequent chapters then use those data sets and others to illustrate the various analytical techniques applicable to such data, including the Cox regression model, the Weibull proportional hazards model, and others. This edition features a more detailed treatment of topics such as parametric models, accelerated failure time models, and analysis of interval-censored data. The author also focuses the software section on the use of SAS, summarising the methods used by the software to generate its output and examining that output in detail. Profusely illustrated with examples and written in the author's trademark, easy-to-follow style, Modelling Survival Data in Medical Research, Second Edition is a thorough, practical guide to survival analysis that reflects current statistical practices....

Author by : Susan Halabi
Languange Used : en
Release Date : 2019-04-24
Publisher by : CRC Press

ISBN :

Description : There is an increasing need for educational resources for statisticians and investigators. Reflecting this, the goal of this book is to provide readers with a sound foundation in the statistical design, conduct, and analysis of clinical trials. Furthermore, it is intended as a guide for statisticians and investigators with minimal clinical trial experience who are interested in pursuing a career in this area. The advancement in genetic and molecular technologies have revolutionized drug development. In recent years, clinical trials have become increasingly sophisticated as they incorporate genomic studies, and efficient designs (such as basket and umbrella trials) have permeated the field. This book offers the requisite background and expert guidance for the innovative statistical design and analysis of clinical trials in oncology. Key Features: Cutting-edge topics with appropriate technical background Built around case studies which give the work a "hands-on" approach Real examples of flaws in previously reported clinical trials and how to avoid them Access to statistical code on the book’s website Chapters written by internationally recognized statisticians from academia and pharmaceutical companies Carefully edited to ensure consistency in style, level, and approach Topics covered include innovating phase I and II designs, trials in immune-oncology and rare diseases, among many others...

Author by : Mark Woodward
Languange Used : en
Release Date : 2013-12-19
Publisher by : CRC Press

ISBN :

Description : Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of epidemiological research. Updated and expanded, this edition shows students how statistical principles and techniques can help solve epidemiological problems. New to the Third Edition New chapter on risk scores and clinical decision rules New chapter on computer-intensive methods, including the bootstrap, permutation tests, and missing value imputation New sections on binomial regression models, competing risk, information criteria, propensity scoring, and splines Many more exercises and examples using both Stata and SAS More than 60 new figures After introducing study design and reviewing all the standard methods, this self-contained book takes students through analytical methods for both general and specific epidemiological study designs, including cohort, case-control, and intervention studies. In addition to classical methods, it now covers modern methods that exploit the enormous power of contemporary computers. The book also addresses the problem of determining the appropriate size for a study, discusses statistical modeling in epidemiology, covers methods for comparing and summarizing the evidence from several studies, and explains how to use statistical models in risk forecasting and assessing new biomarkers. The author illustrates the techniques with numerous real-world examples and interprets results in a practical way. He also includes an extensive list of references for further reading along with exercises to reinforce understanding. Web Resource A wealth of supporting material can be downloaded from the book’s CRC Press web page, including: Real-life data sets used in the text SAS and Stata programs used for examples in the text SAS and Stata programs for special techniques covered Sample size spreadsheet...

Author by : Richard D. Riley
Languange Used : en
Release Date : 2019-01-17
Publisher by : Oxford University Press

ISBN :

Description : "What is going to happen to me?" Most patients ask this question during a clinical encounter with a health professional. As well as learning what problem they have (diagnosis) and what needs to be done about it (treatment), patients want to know about their future health and wellbeing (prognosis). Prognosis research can provide answers to this question and satisfy the need for individuals to understand the possible outcomes of their condition, with and without treatment. Central to modern medical practise, the topic of prognosis is the basis of decision making in healthcare and policy development. It translates basic and clinical science into practical care for patients and populations. Prognosis Research in Healthcare: Concepts, Methods and Impact provides a comprehensive overview of the field of prognosis and prognosis research and gives a global perspective on how prognosis research and prognostic information can improve the outcomes of healthcare. It details how to design, carry out, analyse and report prognosis studies, and how prognostic information can be the basis for tailored, personalised healthcare. In particular, the book discusses how information about the characteristics of people, their health, and environment can be used to predict an individual's future health. Prognosis Research in Healthcare: Concepts, Methods and Impact, addresses all types of prognosis research and provides a practical step-by-step guide to undertaking and interpreting prognosis research studies, ideal for medical students, health researchers, healthcare professionals and methodologists, as well as for guideline and policy makers in healthcare wishing to learn more about the field of prognosis....

Author by : Jürgen Hedderich
Languange Used : de
Release Date : 2018-03-16
Publisher by : Springer-Verlag

ISBN :

Description : Dieses Standardwerk für statistische Methoden in den Biowissenschaften und der Medizin stellt leicht verständlich, anschaulich und praxisnah sowohl Studenten und Dozenten als auch Praktikern alle notwendigen Methoden zur gezielten und umsichtigen Datengewinnung, -analyse und -beurteilung zur Verfügung. Neben Hinweisen und Empfehlungen zur Planung und Auswertung von Studien ermöglichen zahlreiche Beispiele, Querverweise, weiterführende Hinweise sowie ein ausführliches Sachverzeichnis einen breit gefächerten Zugang zur Statistik. Neu in der 16. Auflage sind neben zahlreichen Präzisierungen und vertiefenden Ergänzungen zwei größere Abschnitte. Einmal werden Hinweise auf die Anwendung weiterer spezieller Verteilungsmodelle, wie die halbe Normalverteilung, die gestutzte Normalverteilung und die Extremwertverteilung gegeben. Des Weiteren sind nun auch parametrische Überlebenszeitmodelle (exponentielles, Weibull- und loglogistisches Modell) an Beispieldaten vergleichend dargestellt. Ein neues Verzeichnis der zahlreichen Anwendungsbeispiele erleichtert dem neugierigen Anwender und Praktiker den Einstieg in die Methodenvielfalt der Statistik. Das frei verfügbare Programm R ist ein leicht erlernbares und flexibel einzusetzendes Werkzeug, mit dem der Prozess der Datenanalyse verstanden und gestaltet werden kann. Die Anwendung und der Nutzen des R-Programms werden in diesem Buch anhand zahlreicher Beispiele veranschaulicht. Das Buch dient zum Lernen, Nachschlagen und Anwenden bei unterschiedlichen Vorkenntnissen und breit gestreuten Interessen und richtet sich somit an jeden, der an der Auswertung korrekt gewonnener Daten interessiert ist – insbesondere Biologen, Mediziner, Ingenieure und weitere Naturwissenschaftler – sowohl in der Hochschule als auch in der Praxis....

Author by : Lothar Sachs
Languange Used : de
Release Date : 2006-10-14
Publisher by : Springer-Verlag

ISBN :

Description : Computer unterstützen heutzutage die Anwendung statistischer Methoden. Das Programm R ist hierfür ein leicht erlernbares und flexibel einzusetzendes Werkzeug. Die 12., vollständig neu bearbeitete Auflage veranschaulicht Anwendung und Nutzen anhand zahlreicher durchgerechneter Beispiele. Sie erläutert statistische Ansätze und gibt anschaulich und praxisnah Anwendern mit unterschiedlichen Vorkenntnissen die notwendigen Details, um Daten zu gewinnen, zu beschreiben und zu beurteilen. Neben Hinweisen zur Planung und Auswertung von Studien ermöglichen Beispiele, Querverweise und ein ausführliches Sachverzeichnis den gezielten Zugang zur Statistik....

Author by : Ardo van den Hout
Languange Used : en
Release Date : 2016-11-25
Publisher by : CRC Press

ISBN :

Description : Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book is a three-state process for dementia and survival in the older population. This process is described by an illness-death model with a dementia-free state, a dementia state, and a dead state. Statistical modelling of a multi-state process can investigate potential associations between the risk of moving to the next state and variables such as age, gender, or education. A model can also be used to predict the multi-state process. The methods are for longitudinal data subject to interval censoring. Depending on the definition of a state, it is possible that the time of the transition into a state is not observed exactly. However, when longitudinal data are available the transition time may be known to lie in the time interval defined by two successive observations. Such an interval-censored observation scheme can be taken into account in the statistical inference. Multi-state modelling is an elegant combination of statistical inference and the theory of stochastic processes. Multi-State Survival Models for Interval-Censored Data shows that the statistical modelling is versatile and allows for a wide range of applications....