The book distinctively merges applications from numerous fields such as statistics, biostatistics, the health sciences, and engineering in order to provide a complete introduction to the general statistical use of sample size determination.
Author: Thomas P. Ryan
Publisher: John Wiley & Sons
A comprehensive approach to sample size determination and power with applications for a variety of fields Sample Size Determination and Power features a modern introduction to the applicability of sample size determination and provides a variety of discussions on broad topics including epidemiology, microarrays, survival analysis and reliability, design of experiments, regression, and confidence intervals. The book distinctively merges applications from numerous fields such as statistics, biostatistics, the health sciences, and engineering in order to provide a complete introduction to the general statistical use of sample size determination. Advanced topics including multivariate analysis, clinical trials, and quality improvement are addressed, and in addition, the book provides considerable guidance on available software for sample size determination. Written by a well-known author who has extensively class-tested the material, Sample Size Determination and Power: Highlights the applicability of sample size determination and provides extensive literature coverage Presents a modern, general approach to relevant software to guide sample size determination including CATD (computer-aided trial design) Addresses the use of sample size determination in grant proposals and provides up-to-date references for grant investigators An appealing reference book for scientific researchers in a variety of fields, such as statistics, biostatistics, the health sciences, mathematics, ecology, and geology, who use sampling and estimation methods in their work, Sample Size Determination and Power is also an ideal supplementary text for upper-level undergraduate and graduate-level courses in statistical sampling.
This text describes the following available approaches for estimating sample size in social work research and discusses their strengths and weaknesses: power analysis; heuristics or rules-of-thumb; confidence intervals; computer-intensive ...
Author: Patrick Dattalo
Publisher: Oxford University Press
This text describes the following available approaches for estimating sample size in social work research and discusses their strengths and weaknesses: power analysis; heuristics or rules-of-thumb; confidence intervals; computer-intensive strategies; and ethical and cost considerations.
Determining Power when the sample size is fixed In the above study, if the
sample size is 75 and the effect size is 0.08 let us see what would be the power
in testing the hypothesis. In step 12, select option “Post hoc: Compute achieved ...
Author: J. P. Verma
Publisher: Springer Nature
This book addresses sample size and power in the context of research, offering valuable insights for graduate and doctoral students as well as researchers in any discipline where data is generated to investigate research questions. It explains how to enhance the authenticity of research by estimating the sample size and reporting the power of the tests used. Further, it discusses the issue of sample size determination in survey studies as well as in hypothesis testing experiments so that readers can grasp the concept of statistical errors, minimum detectable difference, effect size, one-tail and two-tail tests and the power of the test. The book also highlights the importance of fixing these boundary conditions in enhancing the authenticity of research findings and improving the chances of research papers being accepted by respected journals. Further, it explores the significance of sample size by showing the power achieved in selected doctoral studies. Procedure has been discussed to fix power in the hypothesis testing experiment. One should usually have power at least 0.8 in the study because having power less than this will have the issue of practical significance of findings. If the power in any study is less than 0.5 then it would be better to test the hypothesis by tossing a coin instead of organizing the experiment. It also discusses determining sample size and power using the freeware G*Power software, based on twenty-one examples using different analyses, like t-test, parametric and non-parametric correlations, multivariate regression, logistic regression, independent and repeated measures ANOVA, mixed design, MANOVA and chi-square.
Sample size calculation plays an important role in clinical research.
Author: Shein-Chung Chow
Publisher: CRC Press
Sample size calculation plays an important role in clinical research. It is not uncommon, however, to observe discrepancies among study objectives (or hypotheses), study design, statistical analysis (or test statistic), and sample size calculation. Focusing on sample size calculation for studies conducted during the various phases of clinical resea
Chapter 5 Power and Sample Size Determination 5.1 Introduction As indicated in
Chapter 1 , one of the major objectives of a bioavailability and bioequivalence
study comparing two formulations ( e.g. , a test formulation and a reference ...
Author: Shein-Chung Chow
Publisher: CRC Press
Preeminent Experts Update a Well-Respected BookTaking into account the regulatory and scientific developments that have occurred since the second edition, Design and Analysis of Bioavailability and Bioequivalence Studies, Third Edition provides a complete presentation of the latest progress of activities and results in bioavailability and bioequiva
A general method for sample size determination in this class of study is described
by Greenland (32). A modified method ... Power and sample size requirements of
studies of this nature are presented by Arkin and Wachtel (35). Additional ...
Author: Elaine R. Monsen
Publisher: American Dietetic Associati
Evidence-based practice depends on well-designed, well-executed research. Now in its second edition, this highly respected guide to dietetics research has been written and edited by the foremost experts in the field. As a guide, this book is invaluable to new and experienced researchers alike. As a reference, Research: Successful Approaches provides practical observations that will make research accessible to all readers.
Sample size determination for case-control studies: the influence of the joint
distribution of exposure and confounder. Stat Med 1990;9:1485–1493. Vaeth M,
Skovlund E. A simple approach to power and sample size calculations in logistic
Author: Stephen B. Hulley
Publisher: Lippincott Williams & Wilkins
This third edition sets the standard for providing a practical guide to planning, tabulating, formulating, and implementing clinical research, with an easy-to-read, uncomplicated presentation. This edition incorporates current research methodology and offers an updated syllabus for conducting a clinical research workshop.
Sample Size Determination and Power Calculation in Clinical Trials 7.1
Prerequisites for Sample Size Determination .......................... 152 7.2 Comparison
of Two Treatment Groups with Continuous Endpoints . 154 7.2.1 Fundamentals .
Author: Ding-Geng (Din) Chen
Publisher: CRC Press
Too often in biostatistical research and clinical trials, a knowledge gap exists between developed statistical methods and the applications of these methods. Filling this gap, Clinical Trial Data Analysis Using R provides a thorough presentation of biostatistical analyses of clinical trial data and shows step by step how to implement the statistical methods using R. The book’s practical, detailed approach draws on the authors’ 30 years of real-world experience in biostatistical research and clinical development. Each chapter presents examples of clinical trials based on the authors’ actual experiences in clinical drug development. Various biostatistical methods for analyzing the data are then identified. The authors develop analysis code step by step using appropriate R packages and functions. This approach enables readers to gain an understanding of the analysis methods and R implementation so that they can use R to analyze their own clinical trial data. With step-by-step illustrations of R implementations, this book shows how to easily use R to simulate and analyze data from a clinical trial. It describes numerous up-to-date statistical methods and offers sound guidance on the processes involved in clinical trials.
Sample size and power estimates A difference to be a difference must make a
difference . ... approximation for mean changes from baseline 9.6 Sample size
and power calculation illustrations 9.6.1 Illustration 1 : Sample size calculation
Author: Curtis L. Meinert
Publisher: Oxford University Press, USA
The definitive reference work on clinical trials, this book presents a wealth of detailed, practical information on the design, conduct, and analysis of both single center and multicenter trials. No other book on clinical trials offers as much detail as Meinert does on such issues as samplesize calculation, stratification and randomization, data systems design, consent form development, publication policies, preparation of funding requests, and reporting procedures.
Sample size determination usually involves the calculation of a required sample
size for some desired statistical properties such as precision and power, whereas
sample size justification provides statistical justification for a selected sample ...
Author: Shein-Chung Chow
Publisher: John Wiley & Sons
Praise for the First Edition of Design and Analysis of Clinical Trials "An excellent book, providing a discussion of the clinical trial process from designing the study through analyzing the data, and to regulatory requirement . . . could easily be used as a classroom text to understand the process in the new drug development area." –Statistical Methods in Medicine A complete and balanced presentation now revised, updated, and expanded As the field of research possibilities expands, the need for a working understanding of how to carry out clinical trials only increases. New developments in the theory and practice of clinical research include a growing body of literature on the subject, new technologies and methodologies, and new guidelines from the International Conference on Harmonization (ICH). Design and Analysis of Clinical Trials, Second Edition provides both a comprehensive, unified presentation of principles and methodologies for various clinical trials, and a well-balanced summary of current regulatory requirements. This unique resource bridges the gap between clinical and statistical disciplines, covering both fields in a lucid and accessible manner. Thoroughly updated from its first edition, the Second Edition of Design and Analysis of Clinical Trials features new topics such as: Clinical trials and regulations, especially those of the ICH Clinical significance, reproducibility, and generalizability Goals of clinical trials and target population New study designs and trial types Sample size determination on equivalence and noninferiority trials, as well as comparing variabilities Also, three entirely new chapters cover: Designs for cancer clinical trials Preparation and implementation of a clinical protocol Data management of a clinical trial Written with the practitioner in mind, the presentation assumes only a minimal mathematical and statistical background for its reader. Instead, the writing emphasizes real-life examples and illustrations from clinical case studies, as well as numerous references-280 of them new to the Second Edition-to the literature. Design and Analysis of Clinical Trials, Second Edition will benefit academic, pharmaceutical, medical, and regulatory scientists/researchers, statisticians, and graduate-level students in these areas by serving as a useful, thorough reference source for clinical research.
Issues regarding power and sample size determination for costeffectiveness trials
are discussed in this chapter. Two broad patterns of approach have been
adopted in the literature, reflecting the analysis of ICERs and the CE plane
versus the ...
Author: Andrew R. Willan
Publisher: John Wiley & Sons
The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research. Statistical Analysis of Cost-Effectiveness Data provides a practical book that synthesises the huge amount of research that has taken place in the area over the last two decades. Comprising an up-to-date overview of the statistical analysis of cost-effectiveness data, the book is supported by numerous worked examples from the author’s own experience. It has been written in a style suitable for medical statisticians and health care professionals alike. Key features include: an overview of statistical methods used in the analysis of cost-effectiveness data. coverage of Bayesian methodology. illustrated throughout by worked examples using real data. suitability for health care professionals with limited statistical knowledge. discussion of software used for data analysis. An essential reference for biostatisticians and health economists engaged in cost-effectiveness analysis of health-care interventions, both in academia and industry. Also of interest to graduate students of biostatistics, public health and economics.
Power and Sample Size Determination FIGURE 8-1 Distribution of X Under He :
u = M A CHAPTER 8 2 In Chapter 6 and Chapter 7 , we presented techniques for
estimation and hypothesis testing , respectively . In Chapter 6 , we saw that ...
Author: Lisa Marie Sullivan
Publisher: Jones & Bartlett Learning
Essentials of Biostatistics provides a fundamental and engaging background for students learning to apply and appropriately interpret biostatistical applications in the field of public health. As the sixth offering in the new Jones and Bartlett Essential Public Health series, the text complements and is consistent with the approach used in the other series titles. Many examples are drawn directly from the authors' remarkable clinical experiences with applied biostatistics, making this text relevant, practical, and interesting for students. The authors are integrally involved with the Framingham Heart Study, and data will be used from that study throughout the textbook.
This suggests that small α levels reduce power. One way to increase power is to
be willing to accept a larger Type I error rate by increasing a priori the α level.
Sample size is also a critical factor in determining the power of a statistical test.
Author: Frederick T. L. Leong
A comprehensive, easy-to-understand guide to the entire research process, this book quickly and efficiently equips advanced students and research assistants to conduct a full-scale investigation. The book is organized around the idea of a 'research script' that is, it follows the standard mode of research planning and design, data collection and analysis, and results writing. The volume contains 35 chapters, some co-authored by advanced graduate students who give their fellow students a touch of the 'real world' adding to the clarity and practicality of many chapters.
size calculation is to estimate the minimal sample size required to meet the
objectives of the study for a fixed probability of type I error to achieve a desired
power, which is defined as 1−β. The power is the probability of rejecting the null
Author: Chul Ahn
Publisher: CRC Press
Accurate sample size calculation ensures that clinical studies have adequate power to detect clinically meaningful effects. This results in the efficient use of resources and avoids exposing a disproportionate number of patients to experimental treatments caused by an overpowered study. Sample Size Calculations for Clustered and Longitudinal Outcomes in Clinical Research explains how to determine sample size for studies with correlated outcomes, which are widely implemented in medical, epidemiological, and behavioral studies. The book focuses on issues specific to the two types of correlated outcomes: longitudinal and clustered. For clustered studies, the authors provide sample size formulas that accommodate variable cluster sizes and within-cluster correlation. For longitudinal studies, they present sample size formulas to account for within-subject correlation among repeated measurements and various missing data patterns. For multiple levels of clustering, the level at which to perform randomization actually becomes a design parameter. The authors show how this can greatly impact trial administration, analysis, and sample size requirement. Addressing the overarching theme of sample size determination for correlated outcomes, this book provides a useful resource for biostatisticians, clinical investigators, epidemiologists, and social scientists whose research involves trials with correlated outcomes. Each chapter is self-contained so readers can explore topics relevant to their research projects without having to refer to other chapters.
The book emphasizes approximate methods, but exact methods are presented when the approximate methods fail. Monte Carlo and bootstrap methods are introduced for situations that don't satisfy the assumptions of the analytical methods.
Author: Paul Mathews
Publisher: Mathews Malnar and Bailey
Sample Size Calculations: Practical Methods for Engineers and Scientists presents power and sample size calculations for common statistical analyses including methods for means, standard deviations, proportions, counts, regression, correlation, and measures of agreement. Topics of special interest to quality engineering professionals include designed experiments, reliability studies, statistical process control, acceptance sampling, process capability analysis, statistical tolerancing, and gage error studies. The book emphasizes approximate methods, but exact methods are presented when the approximate methods fail. Monte Carlo and bootstrap methods are introduced for situations that don't satisfy the assumptions of the analytical methods. Solutions are presented for more than 170 example problems and solutions for selected example problems using PASS, MINITAB, Piface, and R are posted on the Internet.
Subtracting b from 1 provides another probability that plays a critical role in
sample size calculation. Power, or (1 – b), is defined as the probability of correctly
rejecting the null hypothesis when it is false. A commonly used approach for
Author: Professor and Chair Department of Pharmaceutical Health Outcomes and Policy University of Houston College of Pharmacy Houston Texas Rajender R Aparasu, Ed.
Publisher: Jones & Bartlett Publishers
Principles of Research Design and Drug Literature Evaluation is a unique resource that provides a balanced approach covering critical elements of clinical research, biostatistical principles, and scientific literature evaluation techniques for evidence-based medicine. This accessible text provides comprehensive course content that meets and exceeds the curriculum standards set by the Accreditation Council for Pharmacy Education (ACPE). Written by expert authors specializing in pharmacy practice and research, this valuable text will provide pharmacy students and practitioners with a thorough understanding of the principles and practices of drug literature evaluation with a strong grounding in research and biostatistical principles. Principles of Research Design and Drug Literature Evaluation is an ideal foundation for professional pharmacy students and a key resource for pharmacy residents, research fellows, practitioners, and clinical researchers. FEATURES * Chapter Pedagogy: Learning Objectives, Review Questions, References, and Online Resources * Instructor Resources: PowerPoint Presentations, Test Bank, and an Answer Key * Student Resources: a Navigate Companion Website, including Crossword Puzzles, Interactive Flash Cards, Interactive Glossary, Matching Questions, and Web Links From the Foreword: "This book was designed to provide and encourage practitioner s development and use of critical drug information evaluation skills through a deeper understanding of the foundational principles of study design and statistical methods. Because guidance on how a study s limited findings should not be used is rare, practitioners must understand and evaluate for themselves the veracity and implications of the inherently limited primary literature findings they use as sources of drug information to make evidence-based decisions together with their patients. The editors organized the book into three supporting sections to meet their pedagogical goals and address practitioners needs in translating research into practice. Thanks to the editors, authors, and content of this book, you can now be more prepared than ever before for translating research into practice." L. Douglas Ried, PhD, FAPhA Editor-in-Chief Emeritus, Journal of the American Pharmacists Association Professor and Associate Dean for Academic Affairs, College of Pharmacy, University of Texas at Tyler, Tyler, Texas"
In practice, controlling either the type II error rate or the power – holding all other
components fixed – will determine the sample size needed to find a significant
result. Thus, the phrases “sample size determination” and “power analysis” are ...
Author: Roy Sabo
Publisher: Springer Science & Business Media
This textbook will help graduate students in non-statistics disciplines, advanced undergraduate researchers, and research faculty in the health sciences to learn, use and communicate results from many commonly used statistical methods. The material covered, and the manner in which it is presented, describe the entire data analysis process from hypothesis generation to writing the results in a manuscript. Chapters cover, among other topics: one and two-sample proportions, multi-category data, one and two-sample means, analysis of variance, and regression. Throughout the text, the authors explain statistical procedures and concepts using a non-statistical language. This accessible approach is complete with real-world examples and sample write-ups for the Methods and Results sections of scholarly papers. The text also allows for the concurrent use of the programming language R, which is an open-source program created, maintained and updated by the statistical community. R is freely available and easy to download.
Determining sample size has long become a very important issue in clinical trials
because unnecessarily large samples may ... For instance, many studies in
randomized controlled trials have not considered sample size or statistical power
Author: N. Balakrishnan
Publisher: John Wiley & Sons
"Data collection holds an essential part in dictating the future of health sciences and public health, as the compilation of statistics allows researchers and medical practitioners to monitor trends in health status, identify health problems, and evaluate the impact of health policies and programs. Methods and Applications of Statistics in the Life and Health Sciences serves as a single, one-of-a-kind resource on the wide range of statistical methods, techniques, and applications that are applied in modern life and health sciences in research. Specially designed to present encyclopedic content in an accessible and self-contained format, this book outlines thorough coverage of the underlying theory and standard applications to research in related disciplines such as biology, epidemiology, clinical trials, and public health. Uniquely combining established literature with cutting-edge research, this book contains classical works and more than twenty-five new articles and completely revised contributions from the acclaimed Encyclopedia of Statistical Sciences, Second Edition. The result is a compilation of more than eighty articles that explores classic methodology and new topics."--Publisher's description.
Power. and. sample-size. determination. for. survival. analysis. In some cases, we
are stuck with the data we have and, in others, we get to design a data-collection
effort—a study—to produce the data that we will analyze. This chapter ...
Author: Mario Cleves
Publisher: Stata Press
"[This book] provides new researchers with the foundation for understanding the various approaches for analyzing time-to-event data. This book serves not only as a tutorial for those wishing to learn survival analysis but as a ... reference for experienced researchers ..."--Book jacket.
Sample. Size. and. Power. The question of the size of the sample, the number of
observations, to be used in scientific ... For simple comparative experiments,
where one or two groups are involved, the calculation of sample size is relatively
Author: Sanford Bolton
Publisher: CRC Press
Through the use of practical examples and solutions, Pharmaceutical Statistics: Practical and Clinical Applications, Fifth Edition provides the most complete and comprehensive guide to the various statistical applications and research issues in the pharmaceutical industry, particularly in clinical trials and bioequivalence studies.