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Competing Risks and Multistate Models with R covers models that generalize the analysis of time to a single event. Both R and multistate methods are promoted with a focus on nonparametric methods.
This book explains hazard-based analyses of competing risks and multistate data with R. Special emphasis is placed on the interpretation of the results. A unique feature of this book is that readers are encouraged to simulate their own data based on the transition hazards only, which are the key quantities of the subsequent analyses. This simulation-based approach is supplemented with real data examples from studies in clinical medicine where the authors have been involved.
This book is aimed at data analysts, with a background in standard survival analysis, who wish to understand, analyse and interpret more complex event histories with R. It is also suitable for graduate courses in biostatistics, statistics and epidemiological methods with a focus on non- and semiparametric methods.
The real data examples, R packages, and the entire R code used in the book are available online.
Info autore
Mag. Dr. rer.soc.oec. Martin Schumacher MBA, Lektor für betriebliches Finanzmana-gement an der FH MCI in Innsbruck sowie Lektor an den Universitäten Linz und FH Joanneum Graz. Geschäftsführender Gesellschafter der con.os tourismus. consulting gmbh Wien-Linz, einem auf finanzwirtschaftliche Fragestellungen im Tourismus spezialisierten Consulting-Unternehmen, allg. beeideter und konzes-sionierter Sachverständiger für Tourismus.§§Mag.(FH) Manuela Wiesinger, Beraterin der con.os tourismus.consulting, Schwerpunkt betriebswirtschaftl. Finanzplanung und -analyse. Auszeichnung mit dem österr. Tourismusforschungspreis "Tourissimus", dem Graf Chotek Hochschulpreis der Tiroler Sparkasse sowie dem Wissenschaftspreis der WK Tirol für touristische Forschungs-arbeit zum Einsatz von Public Private Partnership Modellen.
Riassunto
This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.
