Statistical Methods For Hospital Monitoring With R
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Statistical Methods For Hospital Monitoring With R
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Author : Anthony Morton
language : en
Publisher: John Wiley & Sons
Release Date : 2013-09-10
Statistical Methods For Hospital Monitoring With R written by Anthony Morton and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-10 with Medical categories.
Hospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. This book provides a suite of functions in R, enabling scientists and data analysts working in infection management and quality improvement departments in hospitals, to analyse their often non-independent data which is frequently in the form of trended, over-dispersed and sometimes auto-correlated time series; this is often difficult to analyse using standard office software. This book provides much-needed guidance on data analysis using R for the growing number of scientists in hospital departments who are responsible for producing reports, and who may have limited statistical expertise. This book explores data analysis using R and is aimed at scientists in hospital departments who are responsible for producing reports, and who are involved in improving safety. Professionals working in the healthcare quality and safety community will also find this book of interest Statistical Methods for Hospital Monitoring with R: Provides functions to perform quality improvement and infection management data analysis. Explores the characteristics of complex systems, such as self-organisation and emergent behaviour, along with their implications for such activities as root-cause analysis and the Pareto principle that seek few key causes of adverse events. Provides a summary of key non-statistical aspects of hospital safety and easy to use functions. Provides R scripts in an accompanying web site enabling analyses to be performed by the reader http://www.wiley.com/go/hospital_monitoring Covers issues that will be of increasing importance in the future, such as, generalised additive models, and complex systems, networks and power laws.
Statistical Methods For Hospital Monitoring With R
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Author : Anthony Morton
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-27
Statistical Methods For Hospital Monitoring With R written by Anthony Morton and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-27 with Medical categories.
Hospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. This book provides a suite of functions in R, enabling scientists and data analysts working in infection management and quality improvement departments in hospitals, to analyse their often non-independent data which is frequently in the form of trended, over-dispersed and sometimes auto-correlated time series; this is often difficult to analyse using standard office software. This book provides much-needed guidance on data analysis using R for the growing number of scientists in hospital departments who are responsible for producing reports, and who may have limited statistical expertise. This book explores data analysis using R and is aimed at scientists in hospital departments who are responsible for producing reports, and who are involved in improving safety. Professionals working in the healthcare quality and safety community will also find this book of interest Statistical Methods for Hospital Monitoring with R: Provides functions to perform quality improvement and infection management data analysis. Explores the characteristics of complex systems, such as self-organisation and emergent behaviour, along with their implications for such activities as root-cause analysis and the Pareto principle that seek few key causes of adverse events. Provides a summary of key non-statistical aspects of hospital safety and easy to use functions. Provides R scripts in an accompanying web site enabling analyses to be performed by the reader http://www.wiley.com/go/hospital_monitoring Covers issues that will be of increasing importance in the future, such as, generalised additive models, and complex systems, networks and power laws.
Statistical Methods For Healthcare Performance Monitoring
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Author : Alex Bottle
language : en
Publisher: CRC Press
Release Date : 2016-08-05
Statistical Methods For Healthcare Performance Monitoring written by Alex Bottle and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-05 with Mathematics categories.
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.
Statistical Methods For Evaluating Safety In Medical Product Development
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Author : A. Lawrence Gould
language : en
Publisher: John Wiley & Sons
Release Date : 2014-12-08
Statistical Methods For Evaluating Safety In Medical Product Development written by A. Lawrence Gould and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-08 with Medical categories.
This book gives professionals in clinical research valuable information on the challenging issues of the design, execution, and management of clinical trials, and how to resolve these issues effectively. It also provides understanding and practical guidance on the application of contemporary statistical methods to contemporary issues in safety evaluation during medical product development. Each chapter provides sufficient detail to the reader to undertake the design and analysis of experiments at various stages of product development, including comprehensive references to the relevant literature. Provides a guide to statistical methods and application in medical product development Assists readers in undertaking design and analysis of experiments at various stages of product development Features case studies throughout the book, as well as, SAS and R code
Introduction To Statistical Methods For Biosurveillance
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Author : Ronald D. Fricker
language : en
Publisher: Cambridge University Press
Release Date : 2013-02-25
Introduction To Statistical Methods For Biosurveillance written by Ronald D. Fricker and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-25 with Mathematics categories.
Presents basic and advanced methods with a focus on demonstrated added value for a broad class of public health surveillance problems.
Crossover Designs
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Author : Kung-Jong Lui
language : en
Publisher: John Wiley & Sons
Release Date : 2016-08-08
Crossover Designs written by Kung-Jong Lui and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-08 with Medical categories.
A comprehensive and practical resource for analyses of crossover designs For ethical reasons, it is vital to keep the number of patients in a clinical trial as low as possible. As evidenced by extensive research publications, crossover design can be a useful and powerful tool to reduce the number of patients needed for a parallel group design in studying treatments for non-curable chronic diseases. This book introduces commonly-used and well-established statistical tests and estimators in epidemiology that can easily be applied to hypothesis testing and estimation of the relative treatment effect for various types of data scale in crossover designs. Models with distribution-free random effects are assumed and hence most approaches considered here are semi-parametric. The book provides clinicians and biostatisticians with the exact test procedures and exact interval estimators, which are applicable even when the number of patients in a crossover trial is small. Systematic discussion on sample size determination is also included, which will be a valuable resource for researchers involved in crossover trial design. Key features: Provides exact test procedures and interval estimators, which are especially of use in small-sample cases. Presents most test procedures and interval estimators in closed-forms, enabling readers to calculate them by use of a pocket calculator or commonly-used statistical packages. Each chapter is self-contained, allowing the book to be used a reference resource. Uses real-life examples to illustrate the practical use of test procedures and estimators Provides extensive exercises to help readers appreciate the underlying theory, learn other relevant test procedures and understand how to calculate the required sample size. Crossover Designs: Testing, Estimation and Sample Size will be a useful resource for researchers from biostatistics, as well as pharmaceutical and clinical sciences. It can also be used as a textbook or reference for graduate students studying clinical experiments.
Bayesian Networks For Probabilistic Inference And Decision Analysis In Forensic Science
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Author : Franco Taroni
language : en
Publisher: John Wiley & Sons
Release Date : 2014-09-22
Bayesian Networks For Probabilistic Inference And Decision Analysis In Forensic Science written by Franco Taroni and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-22 with Mathematics categories.
Bayesian Networks “This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation.” Dr. Ian Evett, Principal Forensic Services Ltd, London, UK Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science Second Edition Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates diffculties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader’s own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.
Advanced Statistical Methods In Process Monitoring Finance And Environmental Science
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Author : Sven Knoth
language : en
Publisher: Springer Nature
Release Date : 2024-10-22
Advanced Statistical Methods In Process Monitoring Finance And Environmental Science written by Sven Knoth and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-22 with Mathematics categories.
This book presents a unique collection of contributions on modern methods and applications in three key areas of statistics, celebrating the significant work of Wolfgang Schmid in this field. It is structured thematically into parts focusing on statistical process monitoring, financial statistics, and spatial statistics with environmetrics, each featuring chapters from leading experts. The opening articles on statistical process monitoring present novel methodologies for the detection of anomalies and control charting techniques, which are crucial for maintaining quality in manufacturing processes. Detailed discussions are included on integrating multivariate statistical methods and real-time monitoring to enhance process reliability and efficiency. The part on financial statistics explores rigorous approaches in financial econometrics, with an emphasis on dynamic modelling of market volatility and risk assessment. Contributions cover advanced asset allocation strategies, leveraging high-dimensional data analysis, and the application of machine learning techniques. Spatial statistics and environmetrics are addressed through innovative research on the statistical analysis of environmental data. This includes the use of geostatistical models and hybrid models that combine traditional statistical techniques with machine learning to improve the prediction of environmental phenomena. Key topics here involve the modelling of extremes and airborne pollutants, the prediction of earthquakes using a smartphone-based sensor network, and reviews of selected topics essential in modern spatial statistics. Each part not only reflects Wolfgang Schmid’s interests and impact in these areas but also provides detailed theoretical and applied studies, demonstrating how these sophisticated statistical methods can be effectively employed in practical scenarios. This makes the book an indispensable resource for researchers and practitioners looking to apply cutting-edge statistical techniques in these complex fields.
Modeling And Analysis Of Compositional Data
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Author : Vera Pawlowsky-Glahn
language : en
Publisher: John Wiley & Sons
Release Date : 2015-03-30
Modeling And Analysis Of Compositional Data written by Vera Pawlowsky-Glahn and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-30 with Mathematics categories.
Modeling and Analysis of Compositional Data presents a practical and comprehensive introduction to the analysis of compositional data along with numerous examples to illustrate both theory and application of each method. Based upon short courses delivered by the authors, it provides a complete and current compendium of fundamental to advanced methodologies along with exercises at the end of each chapter to improve understanding, as well as data and a solutions manual which is available on an accompanying website. Complementing Pawlowsky-Glahn’s earlier collective text that provides an overview of the state-of-the-art in this field, Modeling and Analysis of Compositional Data fills a gap in the literature for a much-needed manual for teaching, self learning or consulting.
Applied Mixed Models In Medicine
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Author : Helen Brown
language : en
Publisher: John Wiley & Sons
Release Date : 2014-12-12
Applied Mixed Models In Medicine written by Helen Brown and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-12 with Medical categories.
A fully updated edition of this key text on mixed models,focusing on applications in medical research The application of mixed models is an increasingly popular wayof analysing medical data, particularly in the pharmaceuticalindustry. A mixed model allows the incorporation of both fixed andrandom variables within a statistical analysis, enabling efficientinferences and more information to be gained from the data. Therehave been many recent advances in mixed modelling, particularlyregarding the software and applications. This third edition ofBrown and Prescott’s groundbreaking text provides an updateon the latest developments, and includes guidance on the use ofcurrent SAS techniques across a wide range of applications. Presents an overview of the theory and applications of mixedmodels in medical research, including the latest developments andnew sections on incomplete block designs and the analysis ofbilateral data. Easily accessible to practitioners in any area where mixedmodels are used, including medical statisticians andeconomists. Includes numerous examples using real data from medical andhealth research, and epidemiology, illustrated with SAS code andoutput. Features the new version of SAS, including new graphics formodel diagnostics and the procedure PROC MCMC. Supported by a website featuring computer code, data sets, andfurther material. This third edition will appeal to applied statisticians workingin medical research and the pharmaceutical industry, as well asteachers and students of statistics courses in mixed models. Thebook will also be of great value to a broad range of scientists,particularly those working in the medical and pharmaceuticalareas.