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Author: David S. Salsburg Publisher: Springer Science & Business Media ISBN: 1461244145 Category : Mathematics Languages : en Pages : 183
Book Description
The reader will soon find that this is more than a "how-to-do-it" book. It describes a philosophical approach to the use of statistics in the analysis of clinical trials. I have come gradually to the position described here, but I have not come that way alone. This approach is heavily influenced by my reading the papers of R.A. Fisher, F.S. Anscombe, F. Mosteller, and J. Neyman. But the most important influences have been those of my medical colleagues, who had important real-life medical questions that needed to be answered. Statistical methods depend on abstract mathematical theorems and often complicated algorithms on the computer. But these are only a means to an end, because in the end the statistical techniques we apply to clinical studies have to provide useful answers. When I was studying martingales and symbolic logic in graduate school, my wife, Fran, had to be left out of the intellectual excitement. But, as she looked on, she kept asking me how is this knowledge useful. That question, what can you do with this? haunted my studies. When I began working in bio statistics, she continued asking me where it was all going, and I had to explain what I was doing in terms of the practical problems that were being ad dressed.
Author: David S. Salsburg Publisher: Springer Science & Business Media ISBN: 1461244145 Category : Mathematics Languages : en Pages : 183
Book Description
The reader will soon find that this is more than a "how-to-do-it" book. It describes a philosophical approach to the use of statistics in the analysis of clinical trials. I have come gradually to the position described here, but I have not come that way alone. This approach is heavily influenced by my reading the papers of R.A. Fisher, F.S. Anscombe, F. Mosteller, and J. Neyman. But the most important influences have been those of my medical colleagues, who had important real-life medical questions that needed to be answered. Statistical methods depend on abstract mathematical theorems and often complicated algorithms on the computer. But these are only a means to an end, because in the end the statistical techniques we apply to clinical studies have to provide useful answers. When I was studying martingales and symbolic logic in graduate school, my wife, Fran, had to be left out of the intellectual excitement. But, as she looked on, she kept asking me how is this knowledge useful. That question, what can you do with this? haunted my studies. When I began working in bio statistics, she continued asking me where it was all going, and I had to explain what I was doing in terms of the practical problems that were being ad dressed.
Author: Institute of Medicine Publisher: National Academies Press ISBN: 0309171148 Category : Medical Languages : en Pages : 221
Book Description
Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.
Author: National Research Council Publisher: National Academies Press ISBN: 030918651X Category : Medical Languages : en Pages : 163
Book Description
Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.
Author: Ramon E. Henkel Publisher: Routledge ISBN: 1351474154 Category : Psychology Languages : en Pages : 541
Book Description
Tests of significance have been a key tool in the research kit of behavioral scientists for nearly fifty years, but their widespread and uncritical use has recently led to a rising volume of controversy about their usefulness. This book gathers the central papers in this continuing debate, brings the issues into clear focus, points out practical problems and philosophical pitfalls involved in using the tests, and provides a benchmark from which further analysis can proceed.The papers deal with some of the basic philosophy of science, mathematical and statistical assumptions connected with significance tests and the problems of the interpretation of test results, but the work is essentially non-technical in its emphasis. The collection succeeds in raising a variety of questions about the value of the tests; taken together, the questions present a strong case for vital reform in test use, if not for their total abandonment in research.The book is designed for practicing researchers-those not extensively trained in mathematics and statistics that must nevertheless regularly decide if and how tests of significance are to be used-and for those training for research. While controversy has been centered in sociology and psychology, and the book will be especially useful to researchers and students in those fields, its importance is great across the spectrum of the scientific disciplines in which statistical procedures are essential-notably political science, economics, and the other social sciences, education, and many biological fields as well.Denton E. Morrison is professor, Department of Sociology, Michigan State University.Ramon E. Henkel is associate professor emeritus, Department of Sociology University of Maryland. He teaches as part of the graduate faculty.
Author: William F. Rosenberger Publisher: John Wiley & Sons ISBN: 1118742249 Category : Mathematics Languages : en Pages : 284
Book Description
Praise for the First Edition “All medical statisticians involved in clinical trials should read this book...” - Controlled Clinical Trials Featuring a unique combination of the applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. Randomization in Clinical Trials: Theory and Practice, Second Edition features: Discussions on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adaptive randomization, including minimization techniques and inference New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Plenty of problem sets, theoretical exercises, and short computer simulations using SAS® to facilitate classroom teaching, simplify the mathematics, and ease readers’ understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics. William F. Rosenberger, PhD, is University Professor and Chairman of the Department of Statistics at George Mason University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and author of over 80 refereed journal articles, as well as The Theory of Response-Adaptive Randomization in Clinical Trials, also published by Wiley. John M. Lachin, ScD, is Research Professor in the Department of Epidemiology and Biostatistics as well as in the Department of Statistics at The George Washington University. A Fellow of the American Statistical Association and the Society for Clinical Trials, Dr. Lachin is actively involved in coordinating center activities for clinical trials of diabetes. He is the author of Biostatistical Methods: The Assessment of Relative Risks, Second Edition, also published by Wiley.
Author: Institute of Medicine Publisher: National Academies Press ISBN: 0309316324 Category : Medical Languages : en Pages : 236
Book Description
Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.
Author: James Le Fanu Publisher: Basic Books ISBN: 9780786709670 Category : Medical Languages : en Pages : 448
Book Description
In the years following World War II, medicine won major battles against smallpox, diphtheria, and polio. In the same period it also produced treatments to control the progress of Parkinson's, rheumatoid arthritis, and schizophrenia. It made realities of open-heart surgery, organ transplants, test-tube babies. Unquestionably, the medical accomplishments of the postwar years stand at the forefront of human endeavor, yet progress in recent decades has slowed nearly to a halt. In this winner of the Los Angeles Times Book Prize, medical doctor and columnist James Le Fanu both surveys the glories of medicine in the postwar years and analyzes the factors that for the past twenty-five years have increasingly widened the gulf between achievement and advancement: the social theories of medicine, ethical issues, and political debates over health care that have hobbled the development of vaccines and discovery of new "miracle" cures. While fully demonstrating the extraordinary progress effected by medical research in the latter half of the twentieth century, Le Fanu also identifies the perils that confront medicine in the twenty-first. 16 pages of black-and-white photographs add to what the Los Angeles Times cited as "a sobering, contrarian challenge" to the "nostrum of medicine as a never-ending font of ‘miracle cures'." "[From] a respected science writer ... important information that ... has been overlooked or ignored by many physicians." —New Republic "Provocative and engrossing and informative." —Houston Chronicle "Marvelously written, meticulously researched ... one of the most thought-provoking and important works to appear in recent years." —Choice
Author: Ramon E. Henkel Publisher: Routledge ISBN: 9781138538535 Category : Languages : en Pages : 347
Book Description
Tests of significance have been a key tool in the research kit of behavioral scientists for nearly fifty years, but their widespread and uncritical use has recently led to a rising volume of controversy about their usefulness. This book gathers the central papers in this continuing debate, brings the issues into clear focus, points out practical problems and philosophical pitfalls involved in using the tests, and provides a benchmark from which further analysis can proceed.The papers deal with some of the basic philosophy of science, mathematical and statistical assumptions connected with significance tests and the problems of the interpretation of test results, but the work is essentially non-technical in its emphasis. The collection succeeds in raising a variety of questions about the value of the tests; taken together, the questions present a strong case for vital reform in test use, if not for their total abandonment in research.The book is designed for practicing researchers-those not extensively trained in mathematics and statistics that must nevertheless regularly decide if and how tests of significance are to be used-and for those training for research. While controversy has been centered in sociology and psychology, and the book will be especially useful to researchers and students in those fields, its importance is great across the spectrum of the scientific disciplines in which statistical procedures are essential-notably political science, economics, and the other social sciences, education, and many biological fields as well.Denton E. Morrison is professor, Department of Sociology, Michigan State University.Ramon E. Henkel is associate professor emeritus, Department of Sociology University of Maryland. He teaches as part of the graduate faculty.