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Applied Statistics in Biomedicine and Clinical Trials Design: Selected Papers from 2013 ICSA/ISBS Joint Statistical Meetings Softcover reprint of the original 1st ed. 2015 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 546 pages, height x width: 235x155 mm, weight: 1162 g, 35 Illustrations, color; 72 Illustrations, black and white; XXIV, 546 p. 107 illus., 35 illus. in color., 1 Paperback / softback
  • Sērija : ICSA Book Series in Statistics
  • Izdošanas datums: 09-Oct-2016
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319362887
  • ISBN-13: 9783319362885
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  • Mīkstie vāki
  • Cena: 136,16 €*
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  • Formāts: Paperback / softback, 546 pages, height x width: 235x155 mm, weight: 1162 g, 35 Illustrations, color; 72 Illustrations, black and white; XXIV, 546 p. 107 illus., 35 illus. in color., 1 Paperback / softback
  • Sērija : ICSA Book Series in Statistics
  • Izdošanas datums: 09-Oct-2016
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319362887
  • ISBN-13: 9783319362885
Citas grāmatas par šo tēmu:
This volume is a unique combination of papers that cover critical topics in biostatistics from academic, government, and industry perspectives. The 6 sections cover Bayesian methods in biomedical research; Diagnostic medicine and classification; Innovative Clinical Trials Design; Modelling and Data Analysis; Personalized Medicine; and Statistical Genomics. The real world applications are in clinical trials, diagnostic medicine and genetics. The peer-reviewed contributions were solicited and selected from some 400 presentations at the annual meeting of the International Chinese Statistical Association (ICSA), held with the International Society for Biopharmaceutical Statistics (ISBS). The conference was held in Bethesda in June 2013, and the material has been subsequently edited and expanded to cover the most recent developments.

Bayesian Methods in Biomedical Research.- Diagnostic Medicine and Classification.- Innovative Clinical Trials Design and Analysis.- Modeling and Data Analysis.- Personalized Medicine.- Statistical Genomics and High-Dimensional Data Analysis.