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Aggiungi al carrelloCondizione: New. Kris Bogaerts, Arnost Komarek and Emmauel LesaffreSurvival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interv.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Survival Analysis with Interval-Censored Data | A Practical Approach with Examples in R, Sas, and Bugs | Kris Bogaerts (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2020 | CRC Press | EAN 9780367572709 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Aggiungi al carrelloCondizione: New. Kris Bogaerts, Arnost Komarek and Emmauel LesaffreSurvival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interv.
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - This book describes methods and software implementations for the analysis of interval-censored data. The authors present the theoretical background for all methods and apply the methods to real data sets. They also provide the R, SAS, and WinBUGS code for all the examples, enabling readers to modify the code and use the methods to solve their own practical problems. In addition, most of the data sets used in the text are available online.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval censoring is often ignored in practice. Many are unaware of the impact of inappropriately dealing with interval censoring. In addition, the necessary software is at times difficult to trace. This book fills in the gap between theory and practice. Features:-Provides an overview of frequentist as well as Bayesian methods.-Include a focus on practical aspects and applications.-Extensively illustrates the methods with examples using R, SAS, and BUGS. Full programs are available on a supplementary website.The authors:Kris Bogaerts is project manager at I-BioStat, KU Leuven. He received his PhD in science (statistics) at KU Leuven on the analysis of interval-censored data. He has gained expertise in a great variety of statistical topics with a focus on the design and analysis of clinical trials.Arnost Komárek is associate professor of statistics at Charles University, Prague. His subject area of expertise covers mainly survival analysis with the emphasis on interval-censored data and classification based on longitudinal data. He is past chair of the Statistical Modelling Society and editor of Statistical Modelling: An International Journal.Emmanuel Lesaffre is professor of biostatistics at I-BioStat, KU Leuven. His research interests include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval-censored data, misclassification issues, and clinical trials. He is the founding chair of the Statistical Modelling Society, past-president of the International Society for Clinical Biostatistics, and fellow of ISI and ASA. 584 pp. Englisch.
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 325.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the last fifty years, interval censoring is often ignored in practice. Many are unaware of the impact of inappropriately dealing with interval censoring. In addition, the necessary software is at times difficult to trace. This book fills in the gap between theory and practice. Features:-Provides an overview of frequentist as well as Bayesian methods.-Include a focus on practical aspects and applications.-Extensively illustrates the methods with examples using R, SAS, and BUGS. Full programs are available on a supplementary website.The authors:Kris Bogaerts is project manager at I-BioStat, KU Leuven. He received his PhD in science (statistics) at KU Leuven on the analysis of interval-censored data. He has gained expertise in a great variety of statistical topics with a focus on the design and analysis of clinical trials.Arnost Komárek is associate professor of statistics at Charles University, Prague. His subject area of expertise covers mainly survival analysis with the emphasis on interval-censored data and classification based on longitudinal data. He is past chair of the Statistical Modelling Society and editor of Statistical Modelling: An International Journal.Emmanuel Lesaffre is professor of biostatistics at I-BioStat, KU Leuven. His research interests include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval-censored data, misclassification issues, and clinical trials. He is the founding chair of the Statistical Modelling Society, past-president of the International Society for Clinical Biostatistics, and fellow of ISI and ASA.