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Real World AI Ethics for Data Scientists Practical Case Studies

Metabolomics Practical Guide to Design and Analysis

Metabolomics Practical Guide to Design and Analysis

Metabolomics is the scientific study of the chemical processes in a living system environment and nutrition. It is a relatively new omics science but the potential applications are wide including medicine personalized medicine and intervention studies food and nutrition plants agriculture and environmental science. The topics presented and discussed in this book are based on the European Molecular Biology Organization (EMBO) practical courses in metabolomics bioinformatics taught to those working in the field from masters to postgraduate students PhDs postdoctoral and early PIs. The book covers the basics and fundamentals of data acquisition and analytical technologies but the primary focus is data handling and data analysis. The mentioning and usage of a particular data analysis tool has been avoided; rather the focus is on the concepts and principles of data processing and analysis. The material has been class-tested and includes lots of examples computing and exercises. Key Features:Provides an overview of qualitative /quantitative methods in metabolomicsOffers an introduction to the key concepts of metabolomics including experimental design and technologyCovers data handling processing analysis data standards and sharingContains lots of examples to illustrate the topicsIncludes contributions from some of the leading researchers in the field of metabolomics with extensive teaching experiences | Metabolomics Practical Guide to Design and Analysis

GBP 44.99
1

Measuring Society

Statistical Design and Analysis of Stability Studies

Statistical Design and Analysis of Stability Studies

The US Food and Drug Administration's Report to the Nation in 2004 and 2005 indicated that one of the top reasons for drug recall was that stability data did not support existing expiration dates. Pharmaceutical companies conduct stability studies to characterize the degradation of drug products and to estimate drug shelf life. Illustrating how stability studies play an important role in drug safety and quality assurance Statistical Design and Analysis of Stability Studies presents the principles and methodologies in the design and analysis of stability studies. After introducing the basic concepts of stability testing the book focuses on short-term stability studies and reviews several methods for estimating drug expiration dating periods. It then compares some commonly employed study designs and discusses both fixed and random batch statistical analyses. Following a chapter on the statistical methods for stability analysis under a linear mixed effects model the book examines stability analyses with discrete responses multiple components and frozen drug products. In addition the author provides statistical methods for dissolution testing and explores current issues and recent developments in stability studies. To ensure the safety of consumers professionals in the field must carry out stability studies to determine the reliability of drug products during their expiration period. This book provides the material necessary for you to perform stability designs and analyses in pharmaceutical research and development.

GBP 44.99
1

Bioequivalence and Statistics in Clinical Pharmacology

Bioequivalence and Statistics in Clinical Pharmacology

Maintaining a practical perspective Bioequivalence and Statistics in Clinical Pharmacology Second Edition explores statistics used in day-to-day clinical pharmacology work. The book is a starting point for those involved in such research and covers the methods needed to design analyze and interpret bioequivalence trials; explores when how and why these studies are performed as part of drug development; and demonstrates the methods using real world examples. Drawing on knowledge gained directly from working in the pharmaceutical industry the authors set the stage by describing the general role of statistics. Once the foundation of clinical pharmacology drug development regulatory applications and the design and analysis of bioequivalence trials are established including recent regulatory changes in design and analysis and in particular sample-size adaptation they move on to related topics in clinical pharmacology involving the use of cross-over designs. These include but are not limited to safety studies in Phase I dose-response trials drug interaction trials food-effect and combination trials QTc and other pharmacodynamic equivalence trials proof-of-concept trials dose-proportionality trials and vaccines trials. This second edition addresses several recent developments in the field including new chapters on adaptive bioequivalence studies scaled average bioequivalence testing and vaccine trials. Purposefully designed to be instantly applicable Bioequivalence and Statistics in Clinical Pharmacology Second Edition provides examples of SAS and R code so that the analyses described can be immediately implemented. The authors have made extensive use of the proc mixed procedures available in SAS.

GBP 44.99
1

New Centrality Measures in Networks How to Take into Account the Parameters of the Nodes and Group Influence of Nodes to Nodes

New Centrality Measures in Networks How to Take into Account the Parameters of the Nodes and Group Influence of Nodes to Nodes

Over the last number of years there has been a growing interest in the analysis of complex networks which describe a wide range of real-world systems in nature and society. Identification of the central elements in such networks is one of the key research areas. Solutions to this problem are important for making strategic decisions and studying the behavior of dynamic processes e. g. epidemic spread. The importance of nodes has been studied using various centrality measures. Generally it should be considered that most real systems are not homogeneous: nodes may have individual attributes and influence each other in groups while connections between nodes may describe different types of relations. Thus critical nodes detection is not a straightforward process. New Centrality Measures in Networks presents a class of new centrality measures which take into account individual attributes of nodes the possibility of group influence and long-range interactions and discusses all their new features. The book provides a wide range of applications of network analysis in several fields – financial networks international migration global trade global food network arms transfers networks of terrorist groups and networks of international journals in economics. Real-world studies of networks indicate that the proposed centrality measures can identify important nodes in different applications. Starting from the basic ideas the development of the indices and their advantages compared to existing centrality measures are presented. Features Built around real-world case studies in a variety of different areas (finance migration trade etc. ) Suitable for students and professional researchers with an interest in complex network analysis Paired with a software package for readers who wish to apply the proposed models of centrality (in Python) available at https://github. com/SergSHV/slric. | New Centrality Measures in Networks How to Take into Account the Parameters of the Nodes and Group Influence of Nodes to Nodes

GBP 48.99
1

Model-Assisted Bayesian Designs for Dose Finding and Optimization Methods and Applications

Model-Assisted Bayesian Designs for Dose Finding and Optimization Methods and Applications

Bayesian adaptive designs provide a critical approach to improve the efficiency and success of drug development that has been embraced by the US Food and Drug Administration (FDA). This is particularly important for early phase trials as they form the basis for the development and success of subsequent phase II and III trials. The objective of this book is to describe the state-of-the-art model-assisted designs to facilitate and accelerate the use of novel adaptive designs for early phase clinical trials. Model-assisted designs possess avant-garde features where superiority meets simplicity. Model-assisted designs enjoy exceptional performance comparable to more complicated model-based adaptive designs yet their decision rules often can be pre-tabulated and included in the protocol—making implementation as simple as conventional algorithm-based designs. An example is the Bayesian optimal interval (BOIN) design the first dose-finding design to receive the fit-for-purpose designation from the FDA. This designation underscores the regulatory agency's support of the use of the novel adaptive design to improve drug development. Features Represents the first book to provide comprehensive coverage of model-assisted designs for various types of dose-finding and optimization clinical trials Describes the up-to-date theory and practice for model-assisted designs Presents many practical challenges issues and solutions arising from early-phase clinical trials Illustrates with many real trial applications Offers numerous tips and guidance on designing dose finding and optimization trials Provides step-by-step illustrations of using software to design trials Develops a companion website (www. trialdesign. org) to provide freely available easy-to-use software to assist learning and implementing model-assisted designs Written by internationally recognized research leaders who pioneered model-assisted designs from the University of Texas MD Anderson Cancer Center this book shows how model-assisted designs can greatly improve the efficiency and simplify the design conduct and optimization of early-phase dose-finding trials. It should therefore be a very useful practical reference for biostatisticians clinicians working in clinical trials and drug regulatory professionals as well as graduate students of biostatistics. Novel model-assisted designs showcase the new KISS principle: Keep it simple and smart! | Model-Assisted Bayesian Designs for Dose Finding and Optimization Methods and Applications

GBP 84.99
1

Games Gambling and Probability An Introduction to Mathematics

Games Gambling and Probability An Introduction to Mathematics

Many experiments have shown the human brain generally has very serious problems dealing with probability and chance. A greater understanding of probability can help develop the intuition necessary to approach risk with the ability to make more informed (and better) decisions. The first four chapters offer the standard content for an introductory probability course albeit presented in a much different way and order. The chapters afterward include some discussion of different games different ideas that relate to the law of large numbers and many more mathematical topics not typically seen in such a book. The use of games is meant to make the book (and course) feel like fun! Since many of the early games discussed are casino games the study of those games along with an understanding of the material in later chapters should remind you that gambling is a bad idea; you should think of placing bets in a casino as paying for entertainment. Winning can obviously be a fun reward but should not ever be expected. Changes for the Second Edition: New chapter on Game Theory New chapter on Sports Mathematics The chapter on Blackjack which was Chapter 4 in the first edition appears later in the book. Reorganization has been done to improve the flow of topics and learning. New sections on Arkham Horror Uno and Scrabble have been added. Even more exercises were added! The goal for this textbook is to complement the inquiry-based learning movement. In my mind concepts and ideas will stick with the reader more when they are motivated in an interesting way. Here we use questions about various games (not just casino games) to motivate the mathematics and I would say that the writing emphasizes a just-in-time mathematics approach. Topics are presented mathematically as questions about the games themselves are posed. Table of Contents Preface1. Mathematics and Probability 2. Roulette and Craps: Expected Value 3. Counting: Poker Hands 4. More Dice: Counting and Combinations and Statistics 5. Game Theory: Poker Bluffing and Other Games 6. Probability/Stochastic Matrices: Board Game Movement 7. Sports Mathematics: Probability Meets Athletics 8. Blackjack: Previous Methods Revisited 9. A Mix of Other Games 10. Betting Systems: Can You Beat the System? 11. Potpourri: Assorted Adventures in Probability Appendices Tables Answers and Selected Solutions Bibliography Biography Dr. David G. Taylor is a professor of mathematics and an associate dean for academic affairs at Roanoke College in southwest Virginia. He attended Lebanon Valley College for his B. S. in computer science and mathematics and went to the University of Virginia for his Ph. D. While his graduate school focus was on studying infinite dimensional Lie algebras he started studying the mathematics of various games in order to have a more undergraduate-friendly research agenda. Work done with two Roanoke College students Heather Cook and Jonathan Marino appears in this book! Currently he owns over 100 different board games and enjoys using probability in his decision-making while playing most of those games. In his spare time he enjoys reading cooking coding playing his board games and spending time with his six-year-old dog Lilly. | Games Gambling and Probability An Introduction to Mathematics

GBP 82.99
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