Comparing Clinical Measurement Methods
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| Author | : Bendix Carstensen |
| Publisher | : John Wiley & Sons |
| Total Pages | : 167 |
| Release | : 2011-06-24 |
| Genre | : Medical |
| ISBN | : 1119957540 |
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.
| Author | : Bendix Carstensen |
| Publisher | : Wiley |
| Total Pages | : 172 |
| Release | : 2010-09-07 |
| Genre | : Medical |
| ISBN | : 9780470694237 |
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.
| Author | : Heleno Bolfarine |
| Publisher | : Springer Nature |
| Total Pages | : 70 |
| Release | : 2020-10-27 |
| Genre | : Mathematics |
| ISBN | : 3030579352 |
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.
| Author | : Agency for Health Care Research and Quality (U.S.) |
| Publisher | : Government Printing Office |
| Total Pages | : 236 |
| Release | : 2013-02-21 |
| Genre | : Medical |
| ISBN | : 1587634236 |
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)
| Author | : Pankaj K. Choudhary |
| Publisher | : John Wiley & Sons |
| Total Pages | : 414 |
| Release | : 2018-01-25 |
| Genre | : Medical |
| ISBN | : 1118553241 |
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.
| Author | : Pankaj Choudhary |
| Publisher | : Springer |
| Total Pages | : 268 |
| Release | : 2015-12-14 |
| Genre | : Mathematics |
| ISBN | : 3319254332 |
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.
| Author | : Institute of Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 221 |
| Release | : 2001-01-01 |
| Genre | : Medical |
| ISBN | : 0309171148 |
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 | : Henrica C. W. de Vet |
| Publisher | : Cambridge University Press |
| Total Pages | : 347 |
| Release | : 2011-08-11 |
| Genre | : Medical |
| ISBN | : 9780521133852 |
The success of the Apgar score demonstrates the astounding power of an appropriate clinical instrument. This down-to-earth book provides practical advice, underpinned by theoretical principles, on developing and evaluating measurement instruments in all fields of medicine. It equips you to choose the most appropriate instrument for specific purposes. The book covers measurement theories, methods and criteria for evaluating and selecting instruments. It provides methods to assess measurement properties, such as reliability, validity and responsiveness, and interpret the results. Worked examples and end-of-chapter assignments use real data and well-known instruments to build your skills at implementation and interpretation through hands-on analysis of real-life cases. All data and solutions are available online. This is a perfect course book for students and a perfect companion for professionals/researchers in the medical and health sciences who care about the quality and meaning of the measurements they perform.
| Author | : Leif E Peterson |
| Publisher | : Springer |
| Total Pages | : 195 |
| Release | : 2013-05-22 |
| Genre | : Computers |
| ISBN | : 3642383424 |
This book constitutes the refereed proceedings of the 9th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2012, held in Houston, TX, USA during in July 2012. The 16 revised full papers presented were carefully reviewed and selected from 23 submissions. The papers are organized in topical sections on relativistic heavy ions and DNA damage; image segmentation; proteomics; RNA and DNA sequence analysis; RNA, DNA, and SNP microarrays; semi-supervised/unsupervised cluster analysis.
| Author | : Richard Chandler |
| Publisher | : John Wiley & Sons |
| Total Pages | : 348 |
| Release | : 2011-03-25 |
| Genre | : Mathematics |
| ISBN | : 111999196X |
The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.
