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Biomathematics. Biometry. Biostatistics --- Mathematical statistics --- Analyse sequentielle --- Sequential analysis --- Sequentiele analyse --- Drugs --- Testing --- Statistical methods --- Drugs - Testing - Statistical methods. --- Sequential analysis.

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In clinical medicine appropriate statistics has become indispensable to evaluate treatment effects. Randomized controlled trials are currently the only trials that truly provide evidence-based medicine. Evidence based medicine has become crucial to optimal treatment of patients. We can define randomized controlled trials by using Christopher J. Bulpitt’s definition “a carefully and ethically designed experiment which includes the provision of adequate and appropriate controls by a process of randomization, so that precisely framed questions can be answered”. The answers given by randomized controlled trials constitute at present the way how patients should be clinically managed. In the setup of such randomized trial one of the most important issues is the statistical basis. The randomized trial will never work when the statistical grounds and analyses have not been clearly defined beforehand. All endpoints should be clearly defined in order to perform appropriate power calculations. Based on these power calculations the exact number of available patients can be calculated in order to have a sufficient quantity of individuals to have the predefined questions answered. Therefore, every clinical physician should be capable to understand the statistical basis of well performed clinical trials. It is therefore a great pleasure that Drs. T. J. Cleophas, A. H. Zwinderman, and T. F. Cleophas have published a book on statistical analysis of clinical trials. The book entitled “Statistics Applied to Clinical Trials” is clearly written and makes complex issues in statistical analysis transparant.

Clinical trials --Statistical methods. --- Drugs --Testing --Statistical methods. --- Drugs --- Clinical trials --- Clinical Trials as Topic --- Data Interpretation, Statistical --- Methods --- Investigative Techniques --- Evaluation Studies as Topic --- Epidemiologic Study Characteristics as Topic --- Decision Support Techniques --- Health Care Evaluation Mechanisms --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Epidemiologic Methods --- Public Health --- Quality of Health Care --- Environment and Public Health --- Health Care Quality, Access, and Evaluation --- Health Care --- Pharmacy, Therapeutics, & Pharmacology --- Medical Research --- Mathematical Statistics --- Medicine --- Mathematics --- Health & Biological Sciences --- Physical Sciences & Mathematics --- Statistical methods --- Testing --- Statistical methods. --- Medicaments --- Medications --- Medicine (Drugs) --- Medicines (Drugs) --- Pharmaceuticals --- Prescription drugs --- Mathematics. --- Probabilities. --- Statistics. --- Probability Theory and Stochastic Processes. --- Biomedicine general. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistics, general. --- Bioactive compounds --- Medical supplies --- Pharmacopoeias --- Chemotherapy --- Materia medica --- Pharmacology --- Pharmacy --- Distribution (Probability theory. --- Medicine. --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Clinical sciences --- Medical profession --- Human biology --- Life sciences --- Medical sciences --- Pathology --- Physicians --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Statistics . --- Biomedicine, general. --- Health Workforce --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Drugs - Testing - Statistical methods --- Clinical trials - Statistical methods

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Thanks to the omnipresent computer, current statistics can include data files of many thousands of values, and can perform any exploratory analysis in less than seconds. This development, however fascinating, generally does not lead to simple results. We should not forget that clinical studies are, mostly, for confirming prior hypotheses based on sound arguments, and the simplest tests provide the best power and are adequate for such studies. In the past few years the authors of this 5th edition, as teachers and research supervisors in academic and top-clinical facilities, have been able to closely observe the latest developments in the field of clinical data analysis, and they have been able to assess their performance. In this 5th edition the 47 chapters of the previous edition have been maintained and upgraded according to the current state of the art, and 20 novel chapters have been added after strict selection of the most valuable and promising novel methods. The novel methods are explained using practical examples and step-by-step analyses readily accessible for non-mathematicians. All of the novel chapters have been internationally published by the authors in peer-reviewed journal, including the American Journal of Therapeutics, the European Journal of Clinical Investigation, The International journal of Clinical Pharmacology and therapeutics, and other journals, and permission is granted by all of them to use this material in the current book. We should add that the authors are well-qualified in their fields of knowledge. Professor Zwinderman is president-elect of the International Society of Biostatistics, and Professor Cleophas is past-president of the American College of Angiology. From their expertise they should be able to make adequate selections of modern methods for clinical data analysis for the benefit of physicians, students, and investigators. The authors, although from a different discipline, one clinician and one statistician, have been working and publishing together for over 10 years, and their research of statistical methodology can be characterized as a continued effort to demonstrate that statistics is not mathematics but rather a discipline at the interface of biology and mathematics. They firmly believe that any reader can benefit from this clinical approach to statistical data analysis.

Clinical trials -- Statistical methods. --- Clinical Trials as Topic -- methods. --- Data Interpretation, Statistical. --- Drugs -- Testing -- Statistical methods. --- Statistics as Topic --- Evaluation Studies as Topic --- Decision Support Techniques --- Epidemiologic Study Characteristics as Topic --- Epidemiologic Methods --- Health Care Evaluation Mechanisms --- Investigative Techniques --- Medical Informatics Applications --- Quality of Health Care --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Public Health --- Medical Informatics --- Environment and Public Health --- Information Science --- Health Care Quality, Access, and Evaluation --- Health Care --- Data Interpretation, Statistical --- Clinical Trials as Topic --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Statistics. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Medicine. --- Laboratory medicine. --- Internal medicine. --- Biomedicine. --- Biomedicine general. --- Laboratory Medicine. --- Statistics, general. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Internal Medicine. --- Econometrics --- Medical laboratories. --- Medicine, Internal --- Medicine --- Diagnosis, Laboratory --- Health facilities --- Laboratories --- Clinical sciences --- Medical profession --- Human biology --- Life sciences --- Medical sciences --- Pathology --- Physicians --- Statistics . --- Biomedicine, general. --- Health Workforce --- Clinical medicine --- Clinical pathology --- Diagnostic laboratory tests --- Laboratory diagnosis --- Laboratory medicine --- Medical laboratory diagnosis --- Diagnosis