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Practical Biostatistics in Translational Healthcare 1st Editon 2019 Softbound at Meripustak

Practical Biostatistics in Translational Healthcare 1st Editon 2019 Softbound by Allen M. Khakshooy, Francesco Chiappelli, Springer

Books from same Author: Allen M. Khakshooy, Francesco Chiappelli

Books from same Publisher: Springer

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  • General Information  
    Author(s)Allen M. Khakshooy, Francesco Chiappelli
    PublisherSpringer
    Edition1st Edition
    ISBN9783662585979
    Pages227
    BindingSoftbound
    LanguageEnglish
    Publish YearFebruary 2019

    Description

    Springer Practical Biostatistics in Translational Healthcare 1st Editon 2019 Softbound by Allen M. Khakshooy, Francesco Chiappelli

    There is an ever-increasing emphasis on evidence-based medicine that is distinguished by systematic crafting of the patient-centered research question, detailed literature searches, and careful appraisal of the resulting evidence. The consensus that ultimately emerges must then be applied in specific clinical settings, and it is to this process that translational effectiveness analysis refers. This portable and easy-to-use handbook is intended as a practical teaching guide on translational effectiveness for students and clinicians. Specifically, it will serve as a primer on patient-centered outcomes research methodology in the health sciences and explain how to acquire and understand the fundamental data that determine which reports are valued as the “best available” evidence. It presents an accessible and readily intelligible set of principles which doctors, dentists, nurses, and insurance carriers will be able to use in the process of health care-related decision-making. ​ Patient-Centered Outcomes Research: Methodology Issues: Realistic deliverable outcomes in Practice-based research networks.- Design Issues: Randomized clinical trials vs. Clustered randomized clinical trials.- Analysis issues: Patient-centered vs. group data analyses & inferences. Bayesian-ism vs. Frequentist-ism in CEERAP: Data and measurements.- Diagnostic and prognostic inferences.- Quantifying the best evidence. Toward TEA: Acceptable sampling.- Meta-analysis.- Validating inferences of clinical relevance.​



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