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Author: Win M. Castle
Publisher:
ISBN: 9780443045424
Category : Biometry
Languages : en
Pages : 0
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Book Description
Many medical and pharmaceutical workers have very little knowledge of statistics. Yet statistics is one of the tools must commonly used in their field. This book aims to give the reader a clear understanding of statistics, particularly in a medical context.The book has been carefully structured to make it easy to use and to learn from. The numerical examples used are simple, to ensure the reader grasps quickly the underlying principles, and the first part of the book is particularly easy reading to encourage the reader initially. The main part of the book dispenses in formation in small doses called 'frames' with questions and answers designed to continously test the reader's grasp of the subject matter. This makes the book particularly useful for self-testing - a powerful way to learn. Moreover, many of the answers feature further explanation or comment to give background to the point being made.As a whole, the book is meant to be read from start to finish (not 'dipped into') so that each point leads on logically, building up the reader's knowledge sequentially. However to cement that knowledge and help revision, each chapter ends with revision summaries covering fully the chapter
Author: Win M. Castle
Publisher:
ISBN: 9780443045424
Category : Biometry
Languages : en
Pages : 0
Get Book Here
Book Description
Many medical and pharmaceutical workers have very little knowledge of statistics. Yet statistics is one of the tools must commonly used in their field. This book aims to give the reader a clear understanding of statistics, particularly in a medical context.The book has been carefully structured to make it easy to use and to learn from. The numerical examples used are simple, to ensure the reader grasps quickly the underlying principles, and the first part of the book is particularly easy reading to encourage the reader initially. The main part of the book dispenses in formation in small doses called 'frames' with questions and answers designed to continously test the reader's grasp of the subject matter. This makes the book particularly useful for self-testing - a powerful way to learn. Moreover, many of the answers feature further explanation or comment to give background to the point being made.As a whole, the book is meant to be read from start to finish (not 'dipped into') so that each point leads on logically, building up the reader's knowledge sequentially. However to cement that knowledge and help revision, each chapter ends with revision summaries covering fully the chapter
Author: Clifton Leaf
Publisher: Simon and Schuster
ISBN: 1476739986
Category : History
Languages : en
Pages : 513
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Book Description
A decade ago Leaf, a cancer survivor himself, began to investigate why we had made such limited progress fighting this terrifying disease. The result is a gripping narrative that reveals why the public's immense investment in research has been badly misspent, why scientists seldom collaborate and share their data, why new drugs are so expensive yet routinely fail, and why our best hope for progress-- brilliant young scientists-- are now abandoning the search for a cure.
Author: Sylvie Chevret
Publisher: John Wiley & Sons
ISBN:
Category : Mathematics
Languages : en
Pages : 344
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Book Description
Dose-finding experiments define the safe dosage of a drug in development, in terms of the quantity given to a patient. Statistical methods play a crucial role in identifying optimal dosage. Used appropriately, these methods provide reliable results and reduce trial duration and costs. In practice, however, dose-finding is often done poorly, with widely used conventional methods frequently being unreliable, leading to inaccurate results. However, there have been many advances in recent years, with new statistical techniques being developed and it is important that these new techniques are utilized correctly. Statistical Methods for Dose-Finding Experiments reviews the main statistical approaches for dose-finding in phase I/II clinical trials and presents practical guidance on their correct use. Includes an introductory section, summarizing the essential concepts in dose-finding. Contains a section on algorithm-based approaches, such as the traditional 3+3 design, and a section on model-based approaches, such as the continual reassessment method. Explains fundamental issues, such as how to stop trials early and how to cope with delayed or ordinal outcomes. Discusses in detail the main websites and software used to implement the methods. Features numerous worked examples making use of real data. Statistical Methods for Dose-Finding Experiments is an important collaboration from the leading experts in the area. Primarily aimed at statisticians and clinicians working in clinical trials and medical research, there is also much to benefit graduate students of biostatistics.
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309171148
Category : Medical
Languages : en
Pages : 221
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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: Luisa T. Fernholz
Publisher: Birkhäuser
ISBN: 3034883269
Category : Mathematics
Languages : en
Pages : 189
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Book Description
Statistics is strongly tied to applications in different scientific disciplines, and the most challenging statistical problems arise from problems in the sciences. In fact, the most innovative statistical research flows from the needs of applications in diverse settings. This volume is a testimony to the crucial role that statistics plays in scientific disciplines such as genetics and environmental sciences, among others. The articles in this volume range from human and agricultural genetic DNA research to carcinogens and chemical concentrations in the environment and to space debris and atmospheric chemistry. Also included are some articles on statistical methods which are sufficiently general and flexible to be applied to many practical situations. The papers were refereed by a panel of experts and the editors of the volume. The contributions are based on the talks presented at the Workshop on Statistics and the Sciences, held at the Centro Stefano Franscini in Ascona, Switzerland, during the week of May 23 to 28, 1999. The meeting was jointly organized by the Swiss Federal Institutes of Technology in Lausanne and Zurich, with the financial support of the Minerva Research Foundation. As the presentations at the workshop helped the participants recognize the po tential role that statistics can play in the sciences, we hope that this volume will help the reader to focus on the central role of statistics in the specific areas presented here and to extrapolate the results to further applications.
Author: Rick H. Hoyle
Publisher: SAGE Publications
ISBN: 1506320082
Category : Social Science
Languages : en
Pages : 394
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Book Description
Newer statistical models, such as structural equation modeling and hierarchical linear modeling, require large sample sizes inappropriate for many research questions or unrealistic for many research arenas. How can researchers get the sophistication and flexibility of large sample studies without the requirement of prohibitively large samples? This book describes and illustrates statistical strategies that meet the sophistication/flexibility criteria for analyzing data from small samples of fewer than 150 cases. Contributions from some of the leading researchers in the field cover the use of multiple imputation software and how it can be used profitably with small data sets and missing data; ways to increase statistical power when sample size cannot be increased; and strategies for computing effect sizes and combining effect sizes across studies. Other contributions describe how to hypothesis test using the bootstrap; methods for pooling effect size indicators from single-case studies; frameworks for drawing inferences from cross-tabulated data; how to determine whether a correlation or covariance matrix warrants structure analysis; and what conditions indicate latent variable modeling is a viable approach to correct for unreliability in the mediator. Other topics include the use of dynamic factor analysis to model temporal processes by analyzing multivariate; time-series data from small numbers of individuals; techniques for coping with estimation problems in confirmatory factor analysis in small samples; how the state space model can be used with surprising accuracy with small data samples; and the use of partial least squares as a viable alternative to covariance-based SEM when the N is small and/or the number of variables in a model is large.
Author: John C. Bailar III
Publisher: CRC Press
ISBN: 0429529600
Category : Mathematics
Languages : en
Pages : 488
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Book Description
This work explains the purpose of statistical methods in medical studies and analyzes the statistical techniques used by clinical investigators, with special emphasis on studies published in "The New England Journal of Medicine". It clarifies fundamental concepts of statistical design and analysis, and facilitates the understanding of research results.
Author: David S. Salsburg
Publisher: CRC Press
ISBN: 1000103382
Category : Mathematics
Languages : en
Pages : 215
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Book Description
This book explains how the computer programs work and why and when they can be applied to problems in toxicology. It discusses the statistical models used and their applications in a general fashion. The book overviews the problems that can arise from the blind use of the statistical models.
Author: David Diez
Publisher:
ISBN: 9781943450046
Category :
Languages : en
Pages :
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Book Description
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
Author: Winifred Mary Castle
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 220
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Book Description
