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Statistics in medicine /

Statistics in Medicine, Third Edition makes medical statistics easy to understand by students, practicing physicians, and researchers. The book begins with databases from clinical medicine and uses such data to give multiple worked-out illustrations of every method. The text opens with how to plan s...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Riffenburgh, R. H. (Robert H.) (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Elsevier/Academic Press, 2012.
Edición:Third edition
Temas:
Acceso en línea:Texto completo

MARC

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520 |a Statistics in Medicine, Third Edition makes medical statistics easy to understand by students, practicing physicians, and researchers. The book begins with databases from clinical medicine and uses such data to give multiple worked-out illustrations of every method. The text opens with how to plan studies from conception to publication and what to do with your data, and follows with step-by-step instructions for biostatistical methods from the simplest levels (averages, bar charts) progressively to the more sophisticated methods now being seen in medical articles (multiple regression, noninferiority testing). Examples are given from almost every medical specialty and from dentistry, nursing, pharmacy, and health care management. A preliminary guide is given to tailor sections of the text to various lengths of biostatistical courses. 
504 |a Includes bibliographical references and indexes. 
505 0 |a Planning studies: from design to publication -- Planning analysis: what do I do with my data? -- Probability and relative frequency -- Distribution -- Descriptive statistics -- Finding probabilities -- Confidence intervals -- Hypothesis testing: concept and practice -- Tests on categorical data -- Risks, odds, and ROC curves -- Tests on ranked data -- Tests on means of continuous data -- Multi-factor ANOVA and ANCOVA -- Tests on variability and distributions -- Managing results of analysis -- Equivalence testing -- Bayesian statistics -- Sample size estimation and meta-analysis -- Modeling concepts and methods -- Clinical decisions based on models -- Regression and correlation -- Multiple and curvilinear regression -- Survival, logistic regression, and cox regression -- Sequential analysis and time series -- Epidemiology -- Measuring association and agreement -- Questionnaires and surveys -- Methods you might meet, but not every day. 
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