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Mixed Effects Models For The Population Approach

Author: Marc Lavielle
Publisher: CRC Press
ISBN: 1482226502
Size: 29.68 MB
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Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects Models Mixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools presents a rigorous framework for describing, implementing, and using mixed effects models. With these models, readers can perform parameter estimation and modeling across a whole population of individuals at the same time. Easy-to-Use Techniques and Tools for Real-World Data Modeling The book first shows how the framework allows model representation for different data types, including continuous, categorical, count, and time-to-event data. This leads to the use of generic methods, such as the stochastic approximation of the EM algorithm (SAEM), for modeling these diverse data types. The book also covers other essential methods, including Markov chain Monte Carlo (MCMC) and importance sampling techniques. The author uses publicly available software tools to illustrate modeling tasks. Methods are implemented in Monolix, and models are visually explored using Mlxplore and simulated using Simulx. Careful Balance of Mathematical Representation and Practical Implementation This book takes readers through the whole modeling process, from defining/creating a parametric model to performing tasks on the model using various mathematical methods. Statisticians and mathematicians will appreciate the rigorous representation of the models and theoretical properties of the methods while modelers will welcome the practical capabilities of the tools. The book is also useful for training and teaching in any field where population modeling occurs.

Exposure Response Modeling

Author: Jixian Wang
Publisher: CRC Press
ISBN: 146657321X
Size: 39.99 MB
Format: PDF, Kindle
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Discover the Latest Statistical Approaches for Modeling Exposure-Response Relationships Written by an applied statistician with extensive practical experience in drug development, Exposure-Response Modeling: Methods and Practical Implementation explores a wide range of topics in exposure-response modeling, from traditional pharmacokinetic-pharmacodynamic (PKPD) modeling to other areas in drug development and beyond. It incorporates numerous examples and software programs for implementing novel methods. The book describes using measurement error models to treat sequential modeling, fitting models with exposure and response driven by complex dynamics, and survival analysis with dynamic exposure history. It also covers Bayesian analysis and model-based Bayesian decision analysis, causal inference to eliminate confounding biases, and exposure-response modeling with response-dependent dose/treatment adjustments (dynamic treatment regimes) for personalized medicine and treatment adaptation. Many examples illustrate the use of exposure-response modeling in experimental toxicology, clinical pharmacology, epidemiology, and drug safety. Some examples demonstrate how to solve practical problems while others help with understanding concepts and evaluating the performance of new methods. The provided SAS and R codes enable readers to test the approaches in their own scenarios. Although application oriented, this book also gives a systematic treatment of concepts and methodology. Applied statisticians and modelers can find details on how to implement new approaches. Researchers can find topics for or applications of their work. In addition, students can see how complicated methodology and models are applied to practical situations.

Bayesian Analysis Made Simple

Author: Phil Woodward
Publisher: CRC Press
ISBN: 1439839557
Size: 33.42 MB
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Although the popularity of the Bayesian approach to statistics has been growing for years, many still think of it as somewhat esoteric, not focused on practical issues, or generally too difficult to understand. Bayesian Analysis Made Simple is aimed at those who wish to apply Bayesian methods but either are not experts or do not have the time to create WinBUGS code and ancillary files for every analysis they undertake. Accessible to even those who would not routinely use Excel, this book provides a custom-made Excel GUI, immediately useful to those users who want to be able to quickly apply Bayesian methods without being distracted by computing or mathematical issues. From simple NLMs to complex GLMMs and beyond, Bayesian Analysis Made Simple describes how to use Excel for a vast range of Bayesian models in an intuitive manner accessible to the statistically savvy user. Packed with relevant case studies, this book is for any data analyst wishing to apply Bayesian methods to analyze their data, from professional statisticians to statistically aware scientists.

The R Book

Author: Michael J. Crawley
Publisher: John Wiley & Sons
ISBN: 1118448960
Size: 35.39 MB
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Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘…if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book…’ (Professional Pensions, July 2007)

Physiologically Based Pharmacokinetic Pbpk Modeling And Simulations

Author: Sheila Annie Peters
Publisher: John Wiley & Sons
ISBN: 1118140303
Size: 79.59 MB
Format: PDF, ePub, Mobi
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The only book dedicated to physiologically-based pharmacokinetic modeling in pharmaceutical science Physiologically-based pharmacokinetic (PBPK) modeling has become increasingly widespread within the pharmaceutical industry over the last decade, but without one dedicated book that provides the information researchers need to learn these new techniques, its applications are severely limited. Describing the principles, methods, and applications of PBPK modeling as used in pharmaceutics, Physiologically-Based Pharmacokinetic (PBPK) Modeling and Simulations fills this void. Connecting theory with practice, the book explores the incredible potential of PBPK modeling for improving drug discovery and development. Comprised of two parts, the book first provides a detailed and systematic treatment of the principles behind physiological modeling of pharmacokinetic processes, inter-individual variability, and drug interactions for small molecule drugs and biologics. The second part looks in greater detail at the powerful applications of PBPK to drug research. Designed for a wide audience encompassing readers looking for a brief overview of the field as well as those who need more detail, the book includes a range of important learning aids. Featuring end-of-chapter keywords for easy reference—a valuable asset for general or novice readers without a PBPK background—along with an extensive bibliography for those looking for further information, Physiologically- Based Pharmacokinetic (PBPK) Modeling and Simulations is the essential single-volume text on one of the hottest topics in the pharmaceutical sciences today.

Statistical Methods For Healthcare Performance Monitoring

Author: Alex Bottle
Publisher: CRC Press
ISBN: 1315355469
Size: 21.95 MB
Format: PDF, ePub
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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 Testing Strategies In The Health Sciences

Author: Albert Vexler
Publisher: CRC Press
ISBN: 1315353016
Size: 51.72 MB
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Statistical Testing Strategies in the Health Sciences provides a compendium of statistical approaches for decision making, ranging from graphical methods and classical procedures through computationally intensive bootstrap strategies to advanced empirical likelihood techniques. It bridges the gap between theoretical statistical methods and practical procedures applied to the planning and analysis of health-related experiments. The book is organized primarily based on the type of questions to be answered by inference procedures or according to the general type of mathematical derivation. It establishes the theoretical framework for each method, with a substantial amount of chapter notes included for additional reference. It then focuses on the practical application for each concept, providing real-world examples that can be easily implemented using corresponding statistical software code in R and SAS. The book also explains the basic elements and methods for constructing correct and powerful statistical decision-making processes to be adapted for complex statistical applications. With techniques spanning robust statistical methods to more computationally intensive approaches, this book shows how to apply correct and efficient testing mechanisms to various problems encountered in medical and epidemiological studies, including clinical trials. Theoretical statisticians, medical researchers, and other practitioners in epidemiology and clinical research will appreciate the book’s novel theoretical and applied results. The book is also suitable for graduate students in biostatistics, epidemiology, health-related sciences, and areas pertaining to formal decision-making mechanisms.

Using R For Introductory Statistics Second Edition

Author: John Verzani
Publisher: CRC Press
ISBN: 1466590734
Size: 80.63 MB
Format: PDF, ePub, Docs
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The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.

Be A Model Communicator

Author: Peter Bonate
ISBN: 9780692323816
Size: 26.60 MB
Format: PDF, Mobi
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Modeling and simulation are increasingly being used in science, business, and engineering to understand and explain complex systems, make predictions, and improve decision-making. Modeling today is not just about developing models. Modelers must be able to efficiently and effectively communicate their results to both laypeople and other scientists for their results to be useful and have impact. Unfortunately, scientists are taught to be boring and academic, all in the name of scientific rigor and professionalism. But it doesn't have to be that way. In this engaging and dynamic book, Dr. Bonate shows step-by-step from planning to delivery how to improve your oral presentations and become a better model communicator. Numerous examples and humorous anecdotes are used to explain concepts and material. Anyone who engages in modeling and simulation will benefit from reading this book.

Medical Biostatistics Third Edition

Author: Abhaya Indrayan
Publisher: CRC Press
ISBN: 1439884145
Size: 45.10 MB
Format: PDF, ePub
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Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Third Edition focuses on the statistical aspects of medicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. The author concludes "Just as results of medical tests, statistical results can be false negative or false positive". This edition provides expanded coverage of topics and includes software illustrations. The author presents step-by-step explanations of statistical methods with the help of numerous real-world examples. Guide charts at the beginning of the book enable quick access to the relevant statistical procedure, and the comprehensive index makes it easier to locate terms of interest.