Comparing Clinical Measurement Methods
Comparing Clinical Measurement Methods

Author: Bendix Carstensen

Publisher: John Wiley & Sons

Published: 2011-06-24

Total Pages: 167

ISBN-13: 1119957540

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This book provides a practical guide to analysis of simple and complex method comparison data, using Stata, SAS and R. It takes the classical Limits of Agreement as a starting point, and presents it in a proper statistical framework. The model serves as a reference for reporting sources of variation and for providing conversion equations and plots between methods for practical use, including prediction uncertainty. Presents a modeling framework for analysis of data and reporting of results from comparing measurements from different clinical centers and/or different methods. Provides the practical tools for analyzing method comparison studies along with guidance on what to report and how to plan comparison studies and advice on appropriate software. Illustrated throughout with computer examples in R. Supported by a supplementary website hosting an R-package that performs the major part of the analyses needed in the area. Examples in SAS and Stata for the most common situations are also provided. Written by an acknowledged expert on the subject, with a long standing experience as a biostatistician in a clinical environment and a track record of delivering training on the subject. Biostatisticians, clinicians, medical researchers and practitioners involved in research and analysis of measurement methods and laboratory investigations will benefit from this book. Students of statistics, biostatistics, and the chemical sciences will also find this book useful.

Comparing Clinical Measurement Methods
Comparing Clinical Measurement Methods

Author: Bendix Carstensen

Publisher: Wiley

Published: 2010-09-07

Total Pages: 172

ISBN-13: 9780470694237

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This book provides a practical guide to analysis of simple and complex method comparison data, using Stata, SAS and R. It takes the classical Limits of Agreement as a starting point, and presents it in a proper statistical framework. The model serves as a reference for reporting sources of variation and for providing conversion equations and plots between methods for practical use, including prediction uncertainty. Presents a modeling framework for analysis of data and reporting of results from comparing measurements from different clinical centers and/or different methods. Provides the practical tools for analyzing method comparison studies along with guidance on what to report and how to plan comparison studies and advice on appropriate software. Illustrated throughout with computer examples in R. Supported by a supplementary website hosting an R-package that performs the major part of the analyses needed in the area. Examples in SAS and Stata for the most common situations are also provided. Written by an acknowledged expert on the subject, with a long standing experience as a biostatistician in a clinical environment and a track record of delivering training on the subject. Biostatisticians, clinicians, medical researchers and practitioners involved in research and analysis of measurement methods and laboratory investigations will benefit from this book. Students of statistics, biostatistics, and the chemical sciences will also find this book useful.

Regression Models for the Comparison of Measurement Methods
Regression Models for the Comparison of Measurement Methods

Author: Heleno Bolfarine

Publisher: Springer Nature

Published: 2020-10-27

Total Pages: 70

ISBN-13: 3030579352

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This book provides an updated account of the regression techniques employed in comparing analytical methods and to test the biases of one method relative to others – a problem commonly found in fields like analytical chemistry, biology, engineering, and medicine. Methods comparison involves a non-standard regression problem; when a method is to be tested in a laboratory, it may be used on samples of suitable reference material, but frequently it is used with other methods on a range of suitable materials whose concentration levels are not known precisely. By presenting a sound statistical background not found in other books for the type of problem addressed, this book complements and extends topics discussed in the current literature. It highlights the applications of the presented techniques with the support of computer routines implemented using the R language, with examples worked out step-by-step. This book is a valuable resource for applied statisticians, practitioners, laboratory scientists, geostatisticians, process engineers, geologists and graduate students.

Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide
Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide

Author: Agency for Health Care Research and Quality (U.S.)

Publisher: Government Printing Office

Published: 2013-02-21

Total Pages: 236

ISBN-13: 1587634236

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This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)

Design and Analysis of Reliability Studies
Design and Analysis of Reliability Studies

Author: Graham Dunn

Publisher: Halsted Press

Published: 1992

Total Pages: 198

ISBN-13: 9780470220658

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Concerned with statistical problems of assessing the dependability, precision and bias of measurements. Using a practical approach, it features enough theoretical material enabling users of relevant techniques to understand why and how the vast array of concepts and methods can be applied. Coverage includes analysis of variance, linear regression and chi-square tests for two-way contingency tables.

Measuring Agreement
Measuring Agreement

Author: Pankaj K. Choudhary

Publisher: John Wiley & Sons

Published: 2018-01-25

Total Pages: 414

ISBN-13: 1118553241

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Presents statistical methodologies for analyzing common types of data from method comparison experiments and illustrates their applications through detailed case studies Measuring Agreement: Models, Methods, and Applications features statistical evaluation of agreement between two or more methods of measurement of a variable with a primary focus on continuous data. The authors view the analysis of method comparison data as a two-step procedure where an adequate model for the data is found, and then inferential techniques are applied for appropriate functions of parameters of the model. The presentation is accessible to a wide audience and provides the necessary technical details and references. In addition, the authors present chapter-length explorations of data from paired measurements designs, repeated measurements designs, and multiple methods; data with covariates; and heteroscedastic, longitudinal, and categorical data. The book also: • Strikes a balance between theory and applications • Presents parametric as well as nonparametric methodologies • Provides a concise introduction to Cohen’s kappa coefficient and other measures of agreement for binary and categorical data • Discusses sample size determination for trials on measuring agreement • Contains real-world case studies and exercises throughout • Provides a supplemental website containing the related datasets and R code Measuring Agreement: Models, Methods, and Applications is a resource for statisticians and biostatisticians engaged in data analysis, consultancy, and methodological research. It is a reference for clinical chemists, ecologists, and biomedical and other scientists who deal with development and validation of measurement methods. This book can also serve as a graduate-level text for students in statistics and biostatistics.

Ordered Data Analysis, Modeling and Health Research Methods
Ordered Data Analysis, Modeling and Health Research Methods

Author: Pankaj Choudhary

Publisher: Springer

Published: 2015-12-14

Total Pages: 268

ISBN-13: 3319254332

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This volume presents an eclectic mix of original research articles in areas covering the analysis of ordered data, stochastic modeling and biostatistics. These areas were featured in a conference held at the University of Texas at Dallas from March 7 to 9, 2014 in honor of Professor H. N. Nagaraja’s 60th birthday and his distinguished contributions to statistics. The articles were written by leading experts who were invited to contribute to the volume from among the conference participants. The volume is intended for all researchers with an interest in order statistics, distribution theory, analysis of censored data, stochastic modeling, time series analysis, and statistical methods for the health sciences, including statistical genetics.

Small Clinical Trials
Small Clinical Trials

Author: Institute of Medicine

Publisher: National Academies Press

Published: 2001-01-01

Total Pages: 221

ISBN-13: 0309171148

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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.

An Introduction to Medical Statistics
An Introduction to Medical Statistics

Author: Martin Bland

Publisher: Oxford University Press

Published: 2015-07-23

Total Pages:

ISBN-13: 0192518399

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Now in its Fourth Edition, An Introduction to Medical Statistics continues to be a 'must-have' textbook for anyone who needs a clear logical guide to the subject. Written in an easy-to-understand style and packed with real life examples, the text clearly explains the statistical principles used in the medical literature. Taking readers through the common statistical methods seen in published research and guidelines, the text focuses on how to interpret and analyse statistics for clinical practice. Using extracts from real studies, the author illustrates how data can be employed correctly and incorrectly in medical research helping readers to evaluate the statistics they encounter and appropriately implement findings in clinical practice. End of chapter exercises, case studies and multiple choice questions help readers to apply their learning and develop their own interpretative skills. This thoroughly revised edition includes new chapters on meta-analysis, missing data, and survival analysis.

Advances in Ranking and Selection, Multiple Comparisons, and Reliability
Advances in Ranking and Selection, Multiple Comparisons, and Reliability

Author: N. Balakrishnan

Publisher: Springer Science & Business Media

Published: 2007-12-28

Total Pages: 439

ISBN-13: 0817644229

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S. Panchapakesan has made significant contributions to ranking and selection and has published in many other areas of statistics, including order statistics, reliability theory, stochastic inequalities, and inference. Written in his honor, the twenty invited articles in this volume reflect recent advances in these areas and form a tribute to Panchapakesan’s influence and impact on these areas. Featuring theory, methods, applications, and extensive bibliographies with special emphasis on recent literature, this comprehensive reference work will serve researchers, practitioners, and graduate students in the statistical and applied mathematics communities.