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" Applied biostatistical principles and concepts : "
Laurens Holmes Jr.
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BL
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| Record Number
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844004
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| Main Entry
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Holmes, Larry,Jr.,1960-
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| Title & Author
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Applied biostatistical principles and concepts : : clinicians' guide to data analysis and interpretation /\ Laurens Holmes Jr.
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| Publication Statement
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Abingdon, Oxon ;New York, NY :: Routledge,, 2018.
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| Page. NO
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1 online resource (xxxiv, 288 pages)
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| ISBN
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1315333163
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: 1315352214
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: 1315369206
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: 1498741207
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: 9781315333168
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: 9781315352213
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: 9781315369204
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: 9781498741200
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1498741193
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9781498741194
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Basics of biomedical and clinical research -- Research design : experimental & non-experimental design -- Population, sample, biostatistical reasoning & probability -- Statistical consideration in clinical research -- Sample size and power estimations -- Single sample statistical inference -- Independent samples statistical inference -- Statistical inference in three or more samples -- Statistical inference involving relationships -- Special topics in modern evidence discovery.
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| Abstract
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"The past three decades have witnessed modern advances in statistical modeling and evidence discovery in biomedical, clinical, and population-based research. With these advances come the challenges in accurate model stipulation and application of models in scientific evidence discoveryApplied Biostatistical Principles and Concepts provides practical knowledge using biological and biochemical specimen/samples in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data from bench to clinics in attempt to improve the health of patients and populations. This book is suitable for both clinicians and health or biological sciences students. It presents the reality in statistical modelling of health research data in a concise manner that will address the issue of "big data" type I error tolerance and probability value, effect size and confidence interval for precision, effect measure modification and interaction as well as confounders, thus allowing for more valid inferences and yielding results that are more reliable, valid and accurate."--Provided by publisher.
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| Subject
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Biometry.
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Medical statistics.
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Medicine-- Research-- Statistical methods.
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Biometry.
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Medical statistics.
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Medicine-- Research-- Statistical methods.
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Biometry.
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Research Design.
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Biostatistics.
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Data Interpretation, Statistical.
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| Dewey Classification
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610.15195
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| LC Classification
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R853.S7H65 2017
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| NLM classification
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WA 950
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