Medical Statistics at a Glance

Aviva Petrie , Caroline Sabin 지음

Wiley-Blackwell 2019년 09월 16일 출간

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Now in its fourth edition, Medical Statistics at a Glance is a concise and accessible introduction to this complex subject. Itprovides clear instruction on how to apply commonly used statistical procedures in an easy-to-read, comprehensive and relevant volume. This new edition continues to be the ideal introductory manual and reference guide to medical statistics, an invaluable companion for statistics lectures and a very useful revision aid.This new edition of Medical Statistics at a Glance: Offers guidance on the practical application of statistical methods in conducting research and presenting results Explains the underlying concepts of medical statistics and presents the key facts without being unduly mathematical Contains succinct self-contained chapters, each with one or more examples, many of them new, to illustrate the use of the methodology described in the chapter. Now provides templates for critical appraisal, checklists for the reporting of randomized controlled trials and observational studies and references to the EQUATOR guidelines for the presentation of study results for many other types of study Includes extensive cross-referencing, flowcharts to aid the choice of appropriate tests, learning objectives for each chapter, a glossary of terms and a glossary of annotated full computer output relevant to the examples in the text Provides cross-referencing to the multiple choice and structured questions in the companion Medical Statistics at a Glance Workbook Medical Statistics at a Glance is a must-have text for undergraduate and post-graduate medical students, medical researchers and biomedical and pharmaceutical professionals.

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Preface Learning objectives Handling data 1 Types of data 2 Data entry 3 Error checking and outliers 4 Displaying data diagrammatically 5 Describing data: the ‘average’ 6 Describing data: the ‘spread’ 7 Theoretical distributions: the Normal distribution 8 Theoretical distributions: other distributions 9 Transformations Sampling and estimation 10 Sampling and sampling distributions 11 Confidence intervals Study design 12 Study design I 13 Study design II 14 Clinical trials 15 Cohort studies 16 Case control studies Hypothesis testing 17 Hypothesis testing 18 Errors in hypothesis testing Basic techniques for analysing data Numerical data 19 Numerical data: a single group 20 Numerical data: two related groups 21 Numerical data: two unrelated groups 22 Numerical data: more than two groups Categorical data 23 Categorical data: a single proportion 24 Categorical data: two proportions 25 Categorical data: more than two categories Regression and correlation 26 Correlation 27 The theory of linear regression 28 Performing a linear regression analysis 29 Multiple linear regression 30 Binary outcomes and logistic regression 31 Rates and Poisson regression 32 Generalized linear models 33 Explanatory variables in statistical models Important considerations 34 Bias and confounding 35 Checking assumptions 36 Sample size calculations 37 Presenting results Additional chapters 38 Diagnostic tools 39 Assessing agreement 40 Evidence-based medicine 41 Methods for clustered data 42 Regression methods for clustered data 43 Systematic reviews and me

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저자(글) Aviva Petrie

Aviva Petrie is Honorary Associate Professor, Biostatistics Unit, UCL Eastman Dental Institute, London, UK.Caroline Sabin is Professor of Medical Statistics and Epidemiology, Centre for Clinical Research, Epidemiology, Modelling and Evaluation, Institute for Global Health, UCL, London, UK.

저자(글) Caroline Sabin