[Download] Statistical Thinking for Non-Statisticians in Drug Regulation (English Edition) de Richard Kay Ebooks, PDF, ePub

[Download] Statistical Thinking for Non-Statisticians in Drug Regulation (English Edition) de Richard Kay Ebooks, PDF, ePub


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Statistical Thinking for Non-Statisticians in Drug Regulation, Second Edition, is a need-to-know guide to understanding statistical methodology, statistical data and results within drug development and clinical trials.It provides non-statisticians working in the pharmaceutical and medical device industries with an accessible introduction to the knowledge they need when working with statistical information and communicating with statisticians. It covers the statistical aspects of design, conduct, analysis and presentation of data from clinical trials in drug regulation and improves the ability to read, understand and critically appraise statistical methodology in papers and reports. As such, it is directly concerned with the day-to-day practice and the regulatory requirements of drug development and clinical trials.Fully conversant with current regulatory requirements, this second edition includes five new chapters covering Bayesian statistics, adaptive designs, observational studies, methods for safety analysis and monitoring and statistics for diagnosis.Authored by a respected lecturer and consultant to the pharmaceutical industry, Statistical Thinking for Non-Statisticians in Drug Regulation is an ideal guide for physicians, clinical research scientists, managers and associates, data managers, medical writers, regulatory personnel and for all non-statisticians working and learning within the pharmaceutical industry.


Statistical thinking for nonstatisticians in drug regulation statistical thinking for nonstatisticians in drug regulation written by a wellknown lecturer and consultant to the pharmaceutical industry this book focuses on the pharmaceutical nonstatistician working within a very strict regulatory environment medical books statistical thinking for nonstatisticians in drug regulation

Statistical thinking for non statisticians in drug regulation statistical thinking for non statisticians in drug regulation statistical thinking for nonstatisticians in drug regulation the flagship course is the twoday or threeday course statistical thinking for nonstatisticians in drug regulation the programme is run by dr kay exclusively on an incompany basis

Statistical thinking for nonstatisticians in drug statistical thinking for nonstatisticians in drug regulation second edition is a needtoknow guide to understanding statistical methodology statistical data and results within drug development and clinical trials it provides nonstatisticians working in the pharmaceutical and medical device industries with an accessible introduction to the knowledge they need when working with

Statistical thinking for non statisticians in drug statistical thinking for non statisticians in drug regulation book based on the course with the same title this highly regarded book now in its second edition provides a clear comprehensive and accessible guide to statistics for the nonstatistician working in the pharmaceutical industry

Statistical thinking for nonstatisticians in drug regulation statistical thinking for nonstatisticians in drug regulation richard kay second edition p cm includes bibliographical references and index isbn 9781118470947 cloth i title dnlm 1 clinical trials as topicmethods 2 drug approval 3 drug industry 4 statistics as topic qv 7714 r853c55 615580724dc23 2014020541

Clinical research statistics for nonstatisticians clinical research statistics for nonstatisticians 1 jennifermarcello seniorbiostatistician jennifer has experience in statistical planning analysis and reporting for phase 1 2 and 3 clinical trials

Statistical thinking for nonstatisticians in drug statistical thinking for clinical trials in drug regulation presents the concepts and statistical thinking behind medical studies with a direct connection to the regulatory environment so that readers can be clear where the statistical methodology fits in with industry requirements