Understanding Clinical Data Analysis，Learning Stat

文件名称: Understanding Clinical Data Analysis

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详细说明：Understanding Clinical Data Analysis，Learning Statistical Principles from Published Clinical Research Ton J Cleophas Aeilko h. zwinderman Understanding U Clinical data Analysis Learning Statistical Principles from Published Clinical research S ringer Ton J Cleophas Aeilko h. zwinderman European Interuniversity College European Interuniversity College of pharmaceutical medicine of pharmaceutical medicine Lyon, france Lyon france Department medicine Department Epidemiology and Biostatistics Albert schweitzer hospital Academic medical center Dordrecht. The Netherlands Amsterdam. The Netherlands ISBN978-3-319-39585-2 ISBN978-3-319-39586-9( e Book) DOⅠ10.1007/978-3-31939586-9 Library of Congress Control Number: 2016950020 o Springer International Publishing Switzerland 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of broadcasting, reproduction on microfilms or in any other physical way, and transmission or informatio the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names registered names trademarks service marks etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland Preface The last decades have witnessed a dramatic and welcome improvement in the meth- ods of drug/treatment evaluation, and, therefore, our ability to use biological, phar- maceutical. and other treatments which will benefit risk ratio. can be better assessed While these changes have had an immense impact on the professional day-to-day lives of medical and health professionals, there are still growing expectations for educational purposes in a more demanding environment The current textbook will. first of all. review the state of the art of clinical trial analysis In order to provide the best accuracy, all statistical issues will be explained with analyses of recent publications from the global medical literature rather than hypothetical examples Relevant novel issues will be addressed likewise, including stepped wedge, adaptive designs, principal-feature analyses, random effects logisti models, modeling for false-positive findings, alpha spending function approach gatekeeping strategies, closure principles, etc Second, this textbook will, particularly, focus on the why-so of clinical data anal ysis. In the past few years, the how-so of current statistical tests has been made more simple thanks to the omnipresent computer providing an abundance of statistical software programs. However, the why-so has been somewhat underemphasized. In search of the latter, questions like what is randomness, what does the scientific method look like, who were the inventors and why is it needed will be answered The 2016 Statistics Module taught at the European Communitys Socrates Project, the European College of Pharmaceutical Medicine, and Claude bernard University, Lyon, France, for the master's program European Diploma of Pharmaceutical Medicine (EUDIPhaRM) was used as a framework. Like earlier textbooks of statistics, from the same authors, published by springer in the years 2012-2015, the current work was written for nonmathematicians, but some high school maths seemed unavoidable Sliedrecht. The Netherland Ton J Cleophas Amsterdam. The Netherlands Aeilko h. zwinderman April 11, 2016 Contents Randomness Introduction 1. 2 Why Mankind Is Not Fond of Thinking in Terms of randomness… Why randomness is good for you 1. 4 The term randomness has a different meanin in different clinical research communications including Research Papers, Study protocols, Consensuses 1. 5 Presence of Randomness in Everyday Life 8 1.6 What Does the scientific method look like. who Were the inventors of it and why is It needed 7 Randomness Is Very Much the Basis of the scientific method 1. 8 Null Hypothesis Testing as Compared to the devil' s Advocacy………………… 1.9 Conclusions 1.10 References 12 2 Randomized and observational research Introduction 2.2 Scientific Rigor........ 13 3 Trial Protocol 14 2.4 Types of Protocols, General.……… ·· 18 2.5 Case-Control Studies.......................... 19 2.6 Cohort Studies 2 2.7 Difference between Odds ratio and risk ratio 2. 8 Other Forms of observational research 24 Randomized research 25 2.10 Making a data file 26 2.11 The Variables in a Data file 27 ontents 2.12 Conclusions 30 2.13 References 30 3 Randomized clinical trials, History, Designs……….33 Introduction 33 Randomized controlled Trials(rcts) Are highly Regulated 34 3.3 Clinical Trial Definition 3.4 History…….… 3.5 Main Use of Clinical Trials: Causal Inference........... 37 3.6 Counterfactual Assertion Experiment 38 3.7 Control in Clinical Trials by randomization............. 39 3. 8 Blinding and placebos 40 3.9 Randomization methods 3.10 Clinical Trial Classifications 46 Experimental Study Designs.….......…….47 3.12 Conclusions 3.13 References 60 4 Randomized Clinical Trials, Analysis Sets, Statistical Analysis, Reporting Issues……… 4.1 Introduction 4.2 Intention to Treat and Per Protocol Analyses………….6 4.2.1 First Example(BMC2007;7:3-10)…… 66 4.2.2 Second Example( Curr Med Res opin 2008 24:2151-7). 4.23 Third Example( Neth med2015;73:23-9)………67 4.3 Statistical Principles.... 4.3.1 Hypotheses 4.3.2 Stratifications 73 4.3.3 Missing values……… 4.3.4 Safety and Tolerability 79 4.4 CONSORT(Consolidated Statement of Randomized trials 4.5 Reporting Issues Including Reporting Bias 4.6 Conclusions 96 4.7 References 96 5 Discrete Data Analysis, Failure Time Data analysis 97 Introduction 7 5.2 Four Step Data Analysis, Different Hypothesis Tests..... 98 5.3 Hypothesis Testing One Sample Z-lest.……………….100 4 Hypothesis Testing Two Sample z-test 104 5.5 Hypothesis Testing Two Sample Chi-Square Test 108 5.6 Hypothesis Testing two Sample Fisher's Exact Test 108 Contents 5.7 Sample Size Considerations for a Two-Group Clinical Trial 109 Hypothesis Testing One Sample two Measurements .110 5.9 Hypothesis Testing One Sample Multiple repeated Measurements .112 5.10 Failure-Time data 113 5.11 Conclusions 117 5.12References.117 6 Quantitative Data Analysis 119 6.1 Intr 6.2 A Real Data Example, Losartan Reduces Aortic Dilatation in Marfan Syndrome 120 6.2.1 Step One, Data S 123 6.2.2 Step Two, Determining the Reliability of the a 127 6.2.3 Step Three, Hypothesis Testing………… 131 6.3 Conclusions ····4·······中 ·中·· 139 6.4 References ·· 140 7 Subgroup analysis. 7.1 Introduction 141 7.2 International guidelines 142 7.3 Regression Models, Many Possibilities, General Form .144 7.4 Regression Modeling, for the Purpose of Increasing Precision 146 7.5 Regression Modeling, to deal with Stratification.….….….….….148 Regression Modeling, to Correct for Confounding. 149 7.7 Regression Modeling, for Assessment of Interactions/ Synergisms 7. 8 Good models 15 Conclusions 155 7.10 References 156 8 Interim Analysis 157 8.1 Introduction................................... 157 8.2 Increased risk of Type I error 159 8.3 Methods for Lowering the Type I Error(a) the Armitage/Pocock Group Sequential Method .160 8.4 Methods for Lowering the Type I Error(a), the Group Sequential Method with a-Spending Function Approach.... 163 8.5 Methods for Lowering the Type I Error(a), the Group Sequential Method with Adaptive designs 170 8.6 Continuous Sequential Trials 172 8.7 Conclusions. .................................................................................175 8.8Re 176

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