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＜電子ブック＞
Bayesian Cost-Effectiveness Analysis with the R package BCEA / by Gianluca Baio, Andrea Berardi, Anna Heath
(Use R!. ISSN:21975744)

版	1st ed. 2017.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2017
大きさ	XVI, 168 p. 55 illus., 26 illus. in color : online resource
著者標目	*Baio, Gianluca author Berardi, Andrea author Heath, Anna author SpringerLink (Online service)
件　名	LCSH:Biometry LCSH:Medical economics LCSH:Mathematical statistics—Data processing LCSH:Medical informatics LCSH:Statistics  LCSH:Practice of medicine LCSH:Hospitals—Administration FREE:Biostatistics FREE:Health Economics FREE:Statistics and Computing FREE:Health Informatics FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Practice and Hospital Management
一般注記	Bayesian analysis in health economics -- Case studies -- BCEA — a R package for Bayesian cost-effectiveness analysis -- Probabilistic sensitivity analysis using BCEA -- BCEAweb: a user-friendly web-app to use BCEA The book provides a description of the process of health economic evaluation and modelling for cost-effectiveness analysis, particularly from the perspective of a Bayesian statistical approach. Some relevant theory and introductory concepts are presented using practical examples and two running case studies. The book also describes in detail how to perform health economic evaluations using the R package BCEA (Bayesian Cost-Effectiveness Analysis). BCEA can be used to post-process the results of a Bayesian cost-effectiveness model and perform advanced analyses producing standardised and highly customisable outputs. It presents all the features of the package, including its many functions and their practical application, as well as its user-friendly web interface. The book is a valuable resource for statisticians and practitioners working in the field of health economics wanting to simplify and standardise their workflow, for example in the preparation of dossiers in support of marketing authorisation, or academic and scientific publications HTTP:URL=https://doi.org/10.1007/978-3-319-55718-2

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