Design And Analysis Of Experiments In The Health Sciences
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Author | : Gerald van Belle |
Publisher | : John Wiley & Sons |
Total Pages | : 256 |
Release | : 2012-07-24 |
Genre | : Mathematics |
ISBN | : 0470127279 |
An accessible and practical approach to the design and analysis of experiments in the health sciences Design and Analysis of Experiments in the Health Sciences provides a balanced presentation of design and analysis issues relating to data in the health sciences and emphasizes new research areas, the crucial topic of clinical trials, and state-of-the- art applications. Advancing the idea that design drives analysis and analysis reveals the design, the book clearly explains how to apply design and analysis principles in animal, human, and laboratory experiments while illustrating topics with applications and examples from randomized clinical trials and the modern topic of microarrays. The authors outline the following five types of designs that form the basis of most experimental structures: Completely randomized designs Randomized block designs Factorial designs Multilevel experiments Repeated measures designs A related website features a wealth of data sets that are used throughout the book, allowing readers to work hands-on with the material. In addition, an extensive bibliography outlines additional resources for further study of the presented topics. Requiring only a basic background in statistics, Design and Analysis of Experiments in the Health Sciences is an excellent book for introductory courses on experimental design and analysis at the graduate level. The book also serves as a valuable resource for researchers in medicine, dentistry, nursing, epidemiology, statistical genetics, and public health.
Author | : Gerald van Belle |
Publisher | : John Wiley & Sons |
Total Pages | : 256 |
Release | : 2012-06-07 |
Genre | : Mathematics |
ISBN | : 1118279719 |
An accessible and practical approach to the design and analysis of experiments in the health sciences Design and Analysis of Experiments in the Health Sciences provides a balanced presentation of design and analysis issues relating to data in the health sciences and emphasizes new research areas, the crucial topic of clinical trials, and state-of-the- art applications. Advancing the idea that design drives analysis and analysis reveals the design, the book clearly explains how to apply design and analysis principles in animal, human, and laboratory experiments while illustrating topics with applications and examples from randomized clinical trials and the modern topic of microarrays. The authors outline the following five types of designs that form the basis of most experimental structures: Completely randomized designs Randomized block designs Factorial designs Multilevel experiments Repeated measures designs A related website features a wealth of data sets that are used throughout the book, allowing readers to work hands-on with the material. In addition, an extensive bibliography outlines additional resources for further study of the presented topics. Requiring only a basic background in statistics, Design and Analysis of Experiments in the Health Sciences is an excellent book for introductory courses on experimental design and analysis at the graduate level. The book also serves as a valuable resource for researchers in medicine, dentistry, nursing, epidemiology, statistical genetics, and public health.
Author | : Douglas C. Montgomery |
Publisher | : Wiley |
Total Pages | : 0 |
Release | : 2005 |
Genre | : Experimental design |
ISBN | : 9780471661597 |
This bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. The new edition includes more software examples taken from the three most dominant programs in the field: Minitab, JMP, and SAS. Additional material has also been added in several chapters, including new developments in robust design and factorial designs. New examples and exercises are also presented to illustrate the use of designed experiments in service and transactional organizations. Engineers will be able to apply this information to improve the quality and efficiency of working systems.
Author | : Richard McCleary |
Publisher | : Oxford University Press |
Total Pages | : 393 |
Release | : 2017 |
Genre | : Business & Economics |
ISBN | : 0190661569 |
Design and Analysis of Time Series Experiments develops methods and models for analysis and interpretation of time series experiments while also addressing recent developments in causal modeling. Unlike other time series texts, it integrates the statistical issues of design, estimation, and interpretation with foundational validity issues. Drawing on examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, this text addresses researchers and graduate students in a wide range of the behavioral, biomedical, and social sciences.
Author | : John Lawson |
Publisher | : CRC Press |
Total Pages | : 629 |
Release | : 2014-12-17 |
Genre | : Mathematics |
ISBN | : 1498728480 |
Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data, shows how to perform the proper analysis of the data,
Author | : Charles S. Reichardt |
Publisher | : Guilford Publications |
Total Pages | : 382 |
Release | : 2019-09-02 |
Genre | : Business & Economics |
ISBN | : 1462540201 |
Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest-posttest, nonequivalent groups, regression discontinuity, and interrupted time-series designs. He details their relative strengths and weaknesses and offers practical advice about their use. Reichardt compares quasi-experiments to randomized experiments and discusses when and why the former might be a better choice. Modern moethods for elaborating a research design to remove bias from estimates of treatment effects are described, as are tactics for dealing with missing data and noncompliance with treatment assignment. Throughout, mathematical equations are translated into words to enhance accessibility.
Author | : Gary W. Oehlert |
Publisher | : W. H. Freeman |
Total Pages | : 600 |
Release | : 2000-01-19 |
Genre | : Mathematics |
ISBN | : 9780716735106 |
Oehlert's text is suitable for either a service course for non-statistics graduate students or for statistics majors. Unlike most texts for the one-term grad/upper level course on experimental design, Oehlert's new book offers a superb balance of both analysis and design, presenting three practical themes to students: • when to use various designs • how to analyze the results • how to recognize various design options Also, unlike other older texts, the book is fully oriented toward the use of statistical software in analyzing experiments.
Author | : Hans-Michael Kaltenbach |
Publisher | : Springer Nature |
Total Pages | : 281 |
Release | : 2021-04-15 |
Genre | : Mathematics |
ISBN | : 3030696413 |
This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields. The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including ‘portable power’ formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice. Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software. Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.
Author | : Helge Toutenburg |
Publisher | : Springer Science & Business Media |
Total Pages | : 507 |
Release | : 2006-05-09 |
Genre | : Mathematics |
ISBN | : 0387227725 |
Unique in commencing with relatively simple statistical concepts and ideas found in most introductory statistical textbooks, this book goes on to cover more material useful for undergraduates and graduate in statistics and biostatistics.
Author | : Basavarajaiah D. M. |
Publisher | : Springer Nature |
Total Pages | : 380 |
Release | : 2020-11-05 |
Genre | : Medical |
ISBN | : 9811582106 |
Recent Statistical techniques are one of the basal evidence for clinical research, a pivotal in handling new clinical research and in evaluating and applying prior research. This book explores various choices of statistical tools and mechanisms, analyses of the associations among different clinical attributes. It uses advanced statistical methods to describe real clinical data sets, when the clinical processes being examined are still in the process. This book also discusses distinct methods for building predictive and probability distribution models in clinical situations and ways to assess the stability of these models and other quantitative conclusions drawn by realistic experimental data sets. Design of experiments and recent posthoc tests have been used in comparing treatment effects and precision of the experimentation. This book also facilitates clinicians towards understanding statistics and enabling them to follow and evaluate the real empirical studies (formulation of randomized control trial) that pledge insight evidence base for clinical practices. This book will be a useful resource for clinicians, postgraduates scholars in medicines, clinical research beginners and academicians to nurture high-level statistical tools with extensive scope.