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Statistical Methods and Analyses for Medical Devices, Pardo


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Цена: 24392.00р.
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Автор: Pardo
Название:  Statistical Methods and Analyses for Medical Devices
ISBN: 9783031261381
Издательство: Springer
Классификация:

ISBN-10: 3031261380
Обложка/Формат: Hardback
Страницы: 380
Вес: 0.76 кг.
Дата издания: 09.05.2023
Язык: English
Издание: 1st ed. 2023
Иллюстрации: 153 illustrations, black and white; xiii, 380 p. 153 illus.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Statistics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book provides a reference for people working in the design, development, and manufacturing of medical devices. While there are no statistical methods specifically intended for medical devices, there are methods that are commonly applied to various problems in the design, manufacturing, and quality control of medical devices. The aim of this book is not to turn everyone working in the medical device industries into mathematical statisticians; rather, the goal is to provide some help in thinking statistically, and knowing where to go to answer some fundamental questions, such as justifying a method used to qualify/validate equipment, or what information is necessary to support the choice of sample sizes. While, there are no statistical methods specifically designed for analysis of medical device data, there are some methods that seem to appear regularly in relation to medical devices. For example, the assessment of receiver operating characteristic curves is fundamental to development of diagnostic tests, and accelerated life testing is often critical for assessing the shelf life of medical device products. Another example is sensitivity/specificity computations are necessary for in-vitro diagnostics, and Taguchi methods can be very useful for designing devices. Even notions of equivalence and noninferiority have different interpretations in the medical device field compared to pharmacokinetics. It contains topics such as dynamic modeling, machine learning methods, equivalence testing, and experimental design, for example. This book is for those with no statistical experience, as well as those with statistical knowledgeable—with the hope to provide some insight into what methods are likely to help provide rationale for choices relating to data gathering and analysis activities for medical devices.
Дополнительное описание: 1. Some Fundamentals – Probability.- 2. Some Fundamentals – Estimation and Inference.- 3. Confidence.- 4. Power and Hypothesis Testing.- 5. Least Squares: Regression and ANOVA.- 6. Product Design – Factorial Experiments.- 7. Process Control.- 8. Inspectio



The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10061.00 р.
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Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Time Series Analysis by State Space Methods

Автор: Durbin, James; Koopman, Siem Jan
Название: Time Series Analysis by State Space Methods
ISBN: 019964117X ISBN-13(EAN): 9780199641178
Издательство: Oxford Academ
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Цена: 21226.00 р.
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Описание: This new edition updates Durbin & Koopman`s important text on the state space approach to time series analysis providing a more comprehensive treatment, including the filtering of nonlinear and non-Gaussian series. The book provides an excellent source for the development of practical courses on time series analysis.

Monte Carlo Statistical Methods

Автор: Christian Robert; George Casella
Название: Monte Carlo Statistical Methods
ISBN: 1441919392 ISBN-13(EAN): 9781441919397
Издательство: Springer
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Цена: 14635.00 р.
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Описание: We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.

A Handbook of Statistical Analyses Using SPSS

Автор: Landau
Название: A Handbook of Statistical Analyses Using SPSS
ISBN: 1138462497 ISBN-13(EAN): 9781138462496
Издательство: Taylor&Francis
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Цена: 30624.00 р.
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Описание: Shows how to conduct a range of univariate and multivariate statistical analysis using the Statistical Package for the Social Sciences, version 11. This title addresses various types of analytical procedure that are applied to data sets, primarily from the social and behavioral sciences areas. It is suitable for researchers in psychology.

Handbook of Statistical Methods and Analyses in Sports

Автор: Jim Albert, Mark E. Glickman, Tim B. Swartz, Ruud H. Koning
Название: Handbook of Statistical Methods and Analyses in Sports
ISBN: 0367331012 ISBN-13(EAN): 9780367331016
Издательство: Taylor&Francis
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Цена: 10411.00 р.
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Описание: This handbook provides overviews of statistical methods in sports, in-depth treatment of critical problems and challenges confronting statistical research in sports. The material in the handbook is organized by major sport followed by a section on other sports and general statistical design and analysis issues that are common to all sports.

Handbook of Statistical Methods and Analyses in Sports

Название: Handbook of Statistical Methods and Analyses in Sports
ISBN: 1498737366 ISBN-13(EAN): 9781498737364
Издательство: Taylor&Francis
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Цена: 30624.00 р.
Наличие на складе: Нет в наличии.

Age-Period-Cohort Models, Approache

Автор: O`Brien
Название: Age-Period-Cohort Models, Approache
ISBN: 1466551534 ISBN-13(EAN): 9781466551534
Издательство: Taylor&Francis
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Цена: 13473.00 р.
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Описание:

Develop a Deep Understanding of the Statistical Issues of APC Analysis

Age-Period-Cohort Models: Approaches and Analyses with Aggregate Data presents an introduction to the problems and strategies for modeling age, period, and cohort (APC) effects for aggregate-level data. These strategies include constrained estimation, the use of age and/or period and/or cohort characteristics, estimable functions, variance decomposition, and a new technique called the s-constraint approach.

See How Common Methods Are Related to Each Other

After a general and wide-ranging introductory chapter, the book explains the identification problem from algebraic and geometric perspectives and discusses constrained regression. It then covers important strategies that provide information that does not directly depend on the constraints used to identify the APC model. The final chapter presents a specific empirical example showing that a combination of the approaches can make a compelling case for particular APC effects.

Get Answers to Questions about the Relationships of Ages, Periods, and Cohorts to Important Substantive Variables

This book incorporates several APC approaches into one resource, emphasizing both their geometry and algebra. This integrated presentation helps researchers effectively judge the strengths and weaknesses of the methods, which should lead to better future research and better interpretation of existing research.

Joint Modeling of Longitudinal and Time-to-Event Data

Автор: Elashoff
Название: Joint Modeling of Longitudinal and Time-to-Event Data
ISBN: 1439807825 ISBN-13(EAN): 9781439807828
Издательство: Taylor&Francis
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Цена: 14851.00 р.
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Описание:

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues.

Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website.

This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

Essentials of a Successful Biostatistical Collaboration

Автор: Earnest
Название: Essentials of a Successful Biostatistical Collaboration
ISBN: 1482226987 ISBN-13(EAN): 9781482226980
Издательство: Taylor&Francis
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Цена: 11636.00 р.
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Описание: The aim of this book is to equip biostatisticians and other quantitative scientists with the necessary skills, knowledge, and habits to collaborate effectively with clinicians in the healthcare field. The book provides valuable insight on where to look for information and material on sample size and statistical techniques commonly used in clinical research, and on how best to communicate with clinicians. It also covers the best practices to adopt in terms of project, time, and data management; relationship with collaborators; etc.

Analysis of Messy Data, Volume III

Автор: Milliken
Название: Analysis of Messy Data, Volume III
ISBN: 158488083X ISBN-13(EAN): 9781584880837
Издательство: Taylor&Francis
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Цена: 26030.00 р.
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Описание: Analysis of covariance is a very useful but often misunderstood methodology for analyzing data where important characteristics of the experimental units are measured but not included as factors in the design. With a balance of theory and examples, this volume provides a guide to this strategy`s techniques, theory, and application.

Statistics in Toxicology Using R

Автор: Hothorn
Название: Statistics in Toxicology Using R
ISBN: 1498701272 ISBN-13(EAN): 9781498701273
Издательство: Taylor&Francis
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Цена: 14545.00 р.
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Описание:

The apparent contradiction between statistical significance and biological relevance has diminished the value of statistical methods as a whole in toxicology. Moreover, recommendations for statistical analysis are imprecise in most toxicological guidelines. Addressing these dilemmas, Statistics in Toxicology Using R explains the statistical analysis of selected experimental data in toxicology and presents assay-specific suggestions, such as for the in vitro micronucleus assay.

Mostly focusing on hypothesis testing, the book covers standardized bioassays for chemicals, drugs, and environmental pollutants. It is organized according to selected toxicological assays, including:

  • Short-term repeated toxicity studies
  • Long-term carcinogenicity assays
  • Studies on reproductive toxicity
  • Mutagenicity assays
  • Toxicokinetic studies

The book also discusses proof of safety (particularly in ecotoxicological assays), toxicogenomics, the analysis of interlaboratory studies and the modeling of dose-response relationships for risk assessment. For each toxicological problem, the author describes the statistics involved, matching data example, R code, and outcomes and their interpretation. This approach allows you to select a certain bioassay, identify the specific data structure, run the R code with the data example, understand the test outcome and interpretation, and replace the data set with your own data and run again.

Statistical Methods for Healthcare Performance Monitoring

Автор: Bottle
Название: Statistical Methods for Healthcare Performance Monitoring
ISBN: 1482246090 ISBN-13(EAN): 9781482246094
Издательство: Taylor&Francis
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Цена: 14851.00 р.
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Описание:

Healthcare is important to everyone, yet large variations in its quality have been well documented both between and within many countries. With demand and expenditure rising, it's more crucial than ever to know how well the healthcare system and all its components - from staff member to regional network - are performing. This requires data, which inevitably differ in form and quality. It also requires statistical methods, the output of which needs to be presented so that it can be understood by whoever needs it to make decisions.

Statistical Methods for Healthcare Performance Monitoring covers measuring quality, types of data, risk adjustment, defining good and bad performance, statistical monitoring, presenting the results to different audiences and evaluating the monitoring system itself. Using examples from around the world, it brings all the issues and perspectives together in a largely non-technical way for clinicians, managers and methodologists.

Statistical Methods for Healthcare Performance Monitoring is aimed at statisticians and researchers who need to know how to measure and compare performance, health service regulators, health service managers with responsibilities for monitoring performance, and quality improvement scientists, including those involved in clinical audits.


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