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Bayesian Statistical Methods
Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models (GLM). The authors include many examples with complete R code and comparisons with analogous frequentist procedures. In addition to the basic concepts of Bayesian inferential methods, the book covers many general topics: Advice on selecting prior distributions Computational methods including Markov chain Monte Carlo (MCMC) Model-comparison and goodness-of-fit measures, including sensitivity to prior...
Metal-Organic Frameworks (MOFs) for Environmental Applications
Metal-Organic Frameworks for Environmental Applications examines this important topic, looking at potential materials and methods for the remediation of pressing pollution issues, such as heavy-metal contaminants in water streams, radioactive waste disposal, marine oil-spillage, the treatment of textile and dye industry effluents, the clean-up of trace amounts of explosives in land and water, and many other topics. This survey of the cutting-edge research and technology of MOFs is an invaluable resource for researchers working in inorganic chemistry and materials science, but it is also ideal for graduate students studying MOFs and their applications. - Examines the applications of metal-org...
Energy Materials
The world is in short supply of energy. Along with environmental factors, it has become crucial for science to provide solutions. Energy Materials is a significant area of research in material science.The various aspects of energy include electrical power, comprising batteries, supercapacitors, thermoelectric energy conversion, photovoltaics, etc. Hydrogen is available in abundance, but catalysts are needed for the catalysis, so catalysts or porous solids have universal appeal in usage and applications. Then there are nuclear energy materials.Overall, energy materials have now captured the most attention worldwide in research and investment. This book covers various sections that are currently exploring energy solutions through materials.
Applied Statistical Designs for the Researcher
Showcasing a discussion of the experimental process and a review of basic statistics, this volume provides methodologies to identify general data distribution, skewness, and outliers. It features a unique classification of the nonparametric analogs of their parametric counterparts according to the strength of the collected data. Applied Statistical Designs for the Researcher discusses three varieties of the Student t test, including a comparison of two different groups with different variances; two groups with the same variance; and a matched, paired group. It introduces the analysis of variance and Latin Square designs and presents screening approaches to comparing two factors and their interactions.
Translational Medicine
Examines Critical Decisions for Transitioning Lab Science to a Clinical SettingThe development of therapeutic pharmaceutical compounds is becoming more expensive, and the success rates for getting such treatments approved for marketing and to the patients is decreasing. As a result, translational medicine (TM) is becoming increasingly important in
Generalized Linear Models
This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers parametric and semiparametric approaches to overdispersed GLMs, presents methods of analyzing correlated binary data using latent variables. It also proposes a semiparametric method to model link functions for binary response data, and identifies areas of important future research and new applications of GLMs.
Metal-Organic Frameworks
Metal-organic frameworks represent a new class of materials that may solve the hydrogen storage problem associated with hydrogen-fueled vehicles. In this first definitive guide to metal-organic framework chemistry, author L. MacGillivray addresses state-of-art developments in this promising technology for alternative fuels. Providing professors, graduate and undergraduate students, structural chemists, physical chemists, and chemical engineers with a historical perspective, as well as the most up-to-date developments by leading experts, Metal-Organic Frameworks examines structure, symmetry, supramolecular chemistry, surface engineering, metal-organometallic frameworks, properties, and reactions.
Medical Biostatistics
Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. This edition includes more topics in order to fill gaps in the previous edition. Various topics have been enlarged and modified as per the new understanding of the subject.
Randomization, Masking, and Allocation Concealment
Randomization, Masking, and Allocation Concealment is indispensable for any trial researcher who wants to use state of the art randomization methods, and also wants to be able to describe these methods correctly. Far too often the subtle nuances that distinguish proper randomization from flawed randomization are completely ignored in trial reports that state only that randomization was used, with no additional information. Experience has shown that in many cases, the type of randomization that was used was flawed. It is only a matter of time before medical journals and regulatory agencies come to realize that we can no longer rely on (or publish) flawed trials, and that flawed randomization ...
Statistical Methods for Immunogenicity Assessment
Develop Effective Immunogenicity Risk Mitigation StrategiesImmunogenicity assessment is a prerequisite for the successful development of biopharmaceuticals, including safety and efficacy evaluation. Using advanced statistical methods in the study design and analysis stages is therefore essential to immunogenicity risk assessment and mitigation stra
