Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages.
Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms.
Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanationsof numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance—all of which are problems that occur frequently in practice.
The text illustrates all parts of the modeling process through many hands-on, real-life examples. And every chapter contains extensive R code for each step of the process. The data sets and corresponding code are available in the book’s companion AppliedPredictiveModeling R package, which is freely available on the CRAN archive.
This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package.
Readers and students interested in implementing the methods should have some basic knowledge of R. And a handful of the more advanced topics require some mathematical knowledge.
Covering the application of techniques including R-index, the Bayesian approach for sensory differences tests, and preference mapping in addition to several other methodologies, this is the comprehensive reference needed by those studying sensory evaluation and applied statistics in agriculture and biological sciences.
Research professionals working with food, beverages, healthcare, cosmetics, and other related areas will find the book a valuable guide to the variety of statistical methods available.Provides comprehensive coverage of statistical techniques in sensory testingIncludes data compiled from real-world experiments Covers the latest in data interpretation and analysisAddresses key methods such as R-index, Thursonian Discriminal Distances, group sequential tests, beta-binomial tests, sensory difference and similarity tests, just-about-right data, signal-to-noise ratio, analysis of cosmetic data, Descriptive Analysis, claims substantiation and preference mapping
The target audience consists of statisticians and other scientists who are responsible for performing statistical analyses within a CMC environment. Basic statistical concepts are addressed in Chapter 2 followed by applications to specific topics related to development and manufacturing. The mathematical level assumes an elementary understanding of statistical methods. The ability to use Excel or statistical packages such as Minitab, JMP, SAS, or R will provide more value to the reader.
The motivation for this book came from an American Association of Pharmaceutical Scientists (AAPS) short course on statistical methods applied to CMC applications presented by four of the authors. One of the course participants asked us for a good reference book, and the only book recommended was written over 20 years ago by Chow and Liu (1995). We agreed that a more recent book would serve a need in our industry.
Since we began this project, an edited book has been published on the same topic by Zhang (2016). The chapters in Zhang discuss statistical methods for CMC as well as drug discovery and nonclinical development. We believe our book complements Zhang by providing more detailed statistical analyses and examples.
Features of the Fourth Edition include:New material on sample size calculations for chance-corrected agreement coefficients, as well as for intraclass correlation coefficients. The researcher will be able to determine the optimal number raters, subjects, and trials per subject.The chapter entitled “Benchmarking Inter-Rater Reliability Coefficients” has been entirely rewritten.The introductory chapter has been substantially expanded to explore possible definitions of the notion of inter-rater reliability.All chapters have been revised to a large extent to improve their readability.
". . . [this book] should be on the shelf of everyone interested in . . . longitudinal data analysis."
—Journal of the American Statistical Association
Features newly developed topics and applications of the analysis of longitudinal data
Applied Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art techniques. The book emphasizes practical, rather than theoretical, aspects of methods for the analysis of diverse types of longitudinal data that can be applied across various fields of study, from the health and medical sciences to the social and behavioral sciences.
The authors incorporate their extensive academic and research experience along with various updates that have been made in response to reader feedback. The Second Edition features six newly added chapters that explore topics currently evolving in the field, including:Fixed effects and mixed effects models Marginal models and generalized estimating equations Approximate methods for generalized linear mixed effects models Multiple imputation and inverse probability weighted methods Smoothing methods for longitudinal data Sample size and power
Each chapter presents methods in the setting of applications to data sets drawn from the health sciences. New problem sets have been added to many chapters, and a related website features sample programs and computer output using SAS, Stata, and R, as well as data sets and supplemental slides to facilitate a complete understanding of the material.
With its strong emphasis on multidisciplinary applications and the interpretation of results, Applied Longitudinal Analysis, Second Edition is an excellent book for courses on statistics in the health and medical sciences at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for researchers and professionals in the medical, public health, and pharmaceutical fields as well as those in social and behavioral sciences who would like to learn more about analyzing longitudinal data.
This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables.
Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include:A chapter on the analysis of correlated outcome data A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion Detailed examples and interpretation of the presented results as well as exercises throughout
Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.
Learn to evaluate and apply statistics in medicine, medical research, and all health-related fields.Emphasis on the basics of biostatistics and epidemiology and the clinical applications in evidence-based medicine and decision-making methods NEW chapter on survey research Expanded discussion of logistic regression, the Cox model, and other multivariate statistical methods Key Concepts in each chapter pinpoint essential information Presenting Problems drawn from studies in the medical literature that illustrate the various statistical methods Downloadable NCSS statistical software, procedures, and data sets from the presenting problems End-of-chapter exercises Multiple-choice final practice exam
Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way.
The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided. For many students and researchers learning to use these methods, this one book may be all they need to conduct and interpret multipredictor regression analyses.
The authors are on the faculty in the Division of Biostatistics, Department of Epidemiology and Biostatistics, University of California, San Francisco, and are authors or co-authors of more than 200 methodological as well as applied papers in the biological and biomedical sciences. The senior author, Charles E. McCulloch, is head of the Division and author of Generalized Linear Mixed Models (2003), Generalized, Linear, and Mixed Models (2000), and Variance Components (1992).
From the reviews:
"This book provides a unified introduction to the regression methods listed in the title...The methods are well illustrated by data drawn from medical studies...A real strength of this book is the careful discussion of issues common to all of the multipredictor methods covered." Journal of Biopharmaceutical Statistics, 2005
"This book is not just for biostatisticians. It is, in fact, a very good, and relatively nonmathematical, overview of multipredictor regression models. Although the examples are biologically oriented, they are generally easy to understand and follow...I heartily recommend the book" Technometrics, February 2006
"Overall, the text provides an overview of regression methods that is particularly strong in its breadth of coverage and emphasis on insight in place of mathematical detail. As intended, this well-unified approach should appeal to students who learn conceptually and verbally." Journal of the American Statistical Association, March 2006
For more than three decades, millions of consumers have trusted The Pill Book to provide official, FDA-approved information on more than 1,800 of the most commonly prescribed drugs in the United States with guidelines from leading pharmacists. Each drug is profiled in a concise, readable, easy-to-understand entry, making The Pill Book the perfect reference when you have questions about the medications your doctor prescribes. Inside you’ll discover
• generic and brand-name listings that can help you save money
• What each drug is for, and how it works
• usual dosages, and what to do if a dose is skipped
• side effects and possible adverse reactions, highlighted for quick reference
• interactions with other drugs and food
• overdose and addiction potential
• alcohol-free and sugar-free medications
• the most popular self-injected medications and their safe handling
• information for seniors, pregnant and breast-feeding women, children, and others with special needs
• cautions and warnings, and when to call your doctor
• 32 pages of actual-size color photographs of prescription pills*
No home should be without this book!
*Not all ereading devices will show the images in color and at the exact size.
“This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one’s personal library.”
—Journal of the American Statistical Association
Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R.
The new edition provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as nontraditional applications, such as regrowth curves, shapes, and images. The book features the latest topics in statistics including modeling of complex clustered or longitudinal data, modeling data with multiple sources of variation, modeling biological variety and heterogeneity, Healthy Akaike Information Criterion (HAIC), parameter multidimensionality, and statistics of image processing.
Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as:Comprehensive theoretical discussions illustrated by examples and figures Over 300 exercises, end-of-section problems, updated data sets, and R subroutines Problems and extended projects requiring simulations in R intended to reinforce material Summaries of major results and general points of discussion at the end of each chapter Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations
Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.
This volume provides formulas and procedures for determination of sample size required not only for testing equality, but also for testing non-inferiority/superiority, and equivalence (similarity) based on both untransformed (raw) data and log-transformed data under a parallel-group design or a crossover design with equal or unequal ratio of treatment allocations. It contains a comprehensive and unified presentation of statistical procedures for sample size calculation that are commonly employed at various phases of clinical development. Each chapter includes, whenever possible, real examples of clinical studies from therapeutic areas such as cardiovascular, central nervous system, anti-infective, oncology, and women's health to demonstrate the clinical and statistical concepts, interpretations, and their relationships and interactions.
The book highlights statistical procedures for sample size calculation and justification that are commonly employed in clinical research and development. It provides clear, illustrated explanations of how the derived formulas and/or statistical procedures can be used.
• Introduces requisite background to using Nonlinear Mixed Effects Modeling (NONMEM), covering data requirements, model building and evaluation, and quality control aspects
• Provides examples of nonlinear modeling concepts and estimation basics with discussion on the model building process and applications of empirical Bayesian estimates in the drug development environment
• Includes detailed chapters on data set structure, developing control streams for modeling and simulation, model applications, interpretation of NONMEM output and results, and quality control
• Has datasets, programming code, and practice exercises with solutions, available on a supplementary website
This new edition of Medical Statistics at a Glance:Presents key facts accompanied by clear and informative tables and diagrams Focuses on illustrative examples which show statistics in action, with an emphasis on the interpretation of computer data analysis rather than complex hand calculations Includes extensive cross-referencing, a comprehensive glossary of terms and flow-charts to make it easier to choose appropriate tests Now provides the learning objectives for each chapter Includes a new chapter on Developing Prognostic Scores Includes new or expanded material on study management, multi-centre studies, sequential trials, bias and different methods to remove confounding in observational studies, multiple comparisons, ROC curves and checking assumptions in a logistic regression analysis The companion website at www.medstatsaag.com contains supplementary material including an extensive reference list and multiple choice questions (MCQs) with interactive answers for self-assessment.
Medical Statistics at a Glance will appeal to all medical students, junior doctors and researchers in biomedical and pharmaceutical disciplines.
Reviews of the previous editions
"The more familiar I have become with this book, the more I appreciate the clear presentation and unthreatening prose. It is now a valuable companion to my formal statistics course."
–International Journal of Epidemiology
"I heartily recommend it, especially to first years, but it's equally appropriate for an intercalated BSc or Postgraduate research. If statistics give you headaches - buy it. If statistics are all you think about - buy it."
"...I unreservedly recommend this book to all medical students, especially those that dislike reading reams of text. This is one book that will not sit on your shelf collecting dust once you have graduated and will also function as a reference book."
–4th Year Medical Student, Barts and the London Chronicle, Spring 2003
Includes practical examples from recent trials
Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple comparison research with an emphasis on pharmaceutical applications. In each chapter, the expert contributors describe important multiplicity problems encountered in pre-clinical and clinical trial settings.
The book begins with a broad introduction from a regulatory perspective to different types of multiplicity problems that commonly arise in confirmatory controlled clinical trials, before giving an overview of the concepts, principles, and procedures of multiple testing. It then presents statistical methods for analyzing clinical dose response studies that compare several dose levels with a control as well as statistical methods for analyzing multiple endpoints in clinical trials. After covering gatekeeping procedures for testing hierarchically ordered hypotheses, the book discusses statistical approaches for the design and analysis of adaptive designs and related confirmatory hypothesis testing problems. The final chapter focuses on the design of pharmacogenomic studies based on established statistical principles. It also describes the analysis of data collected in these studies, taking into account the numerous multiplicity issues that occur.
This volume explains how to solve critical issues in multiple testing encountered in pre-clinical and clinical trial applications. It presents the necessary statistical methodology, along with examples and software code to show how to use the methods in practice.
Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods.
This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures.
Multiple Imputation and its Application:Discusses the issues raised by the analysis of partially observed data, and the assumptions on which analyses rest. Presents a practical guide to the issues to consider when analysing incomplete data from both observational studies and randomized trials. Provides a detailed discussion of the practical use of MI with real-world examples drawn from medical and social statistics. Explores handling non-linear relationships and interactions with multiple imputation, survival analysis, multilevel multiple imputation, sensitivity analysis via multiple imputation, using non-response weights with multiple imputation and doubly robust multiple imputation.
Multiple Imputation and its Application is aimed at quantitative researchers and students in the medical and social sciences with the aim of clarifying the issues raised by the analysis of incomplete data data, outlining the rationale for MI and describing how to consider and address the issues that arise in its application.
The aim of this book is to show how R can be used as the software tool in the development of Six Sigma projects. The book includes a gentle introduction to Six Sigma and a variety of examples showing how to use R within real situations. It has been conceived as a self contained piece. Therefore, it is addressed not only to Six Sigma practitioners, but also to professionals trying to initiate themselves in this management methodology. The book may be used as a text book as well.
This Book:Surveys basic statistical methods used in the genetics and epidemiology literature, including maximum likelihood and least squares. Introduces methods, such as permutation testing and bootstrapping, that are becoming more widely used in both genetic and epidemiological research. Is illustrated throughout with simple examples to clarify the statistical methodology. Explains Bayes’ theorem pictorially. Features exercises, with answers to alternate questions, enabling use as a course text.
Written at an elementary mathematical level so that readers with high school mathematics will find the content accessible. Graduate students studying genetic epidemiology, researchers and practitioners from genetics, epidemiology, biology, medical research and statistics will find this an invaluable introduction to statistics.
New York Times Bestseller
“Not so different in spirit from the way public intellectuals like John Kenneth Galbraith once shaped discussions of economic policy and public figures like Walter Cronkite helped sway opinion on the Vietnam War…could turn out to be one of the more momentous books of the decade.”
—New York Times Book Review
"Nate Silver's The Signal and the Noise is The Soul of a New Machine for the 21st century."
—Rachel Maddow, author of Drift
"A serious treatise about the craft of prediction—without academic mathematics—cheerily aimed at lay readers. Silver's coverage is polymathic, ranging from poker and earthquakes to climate change and terrorism."
—New York Review of Books
Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of FiveThirtyEight.com.
Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future.
In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good—or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary—and dangerous—science.
Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise.
With everything from the health of the global economy to our ability to fight terrorism dependent on the quality of our predictions, Nate Silver’s insights are an essential read.
From the Trade Paperback edition.
* import and preprocessing of data from various sources
* statistical modeling of differential gene expression
* biological metadata
* application of graphs and graph rendering
* machine learning for clustering and classification problems
* gene set enrichment analysis
Each chapter of this book describes an analysis of real data using hands-on example driven approaches. Short exercises help in the learning process and invite more advanced considerations of key topics. The book is a dynamic document. All the code shown can be executed on a local computer, and readers are able to reproduce every computation, figure, and table.
The most up-to-date information about the more than 1,800 most commonly prescribed drugs in the United States:
• Generic and brand-name listings that can help you save money
• What the drug is for, and how it works
• Usual dosages, and what to do if a dose is skipped
• Side effects and possible adverse reactions, highlighted for quick reference
• Interactions with other drugs and food
• Overdose and addiction potential
• Alcohol-free and sugar-free medications
• The most popular self-injected medications and their safe handling
• Information for seniors, pregnant and breast-feeding women, children, and others with special needs
• Cautions and warnings, and when to call your doctor
• 32 pages of actual-size color photographs of prescription pills
From the Trade Paperback edition.
Knowledge flow — A mobile learning platform provides Apps and Books.
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1. Introduction to Pharmacology
5. Drugs affecting on Nervous system
6. Drugs affecting on Central nervous system
7. Drugs affecting on Cardiovascular system
8. Classification of Endocrine system
9. Drugs affecting on Respiratory system
10. Drugs affecting on Gastro intestinal Tract
11. Drugs affecting on Erectile dysfunction
12. Drugs affecting on Erythrocytic
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Author Sebastian Enfield had it all. A loving family, an up-and-coming career at a Fortune 500 company, good friends and an active social life. He was living the proverbial American dream. Until, that is, his life was sidetracked when he became addicted to painkillers. It all started with far-too-easy online purchases of narcotic pills, and eventually Sebastian “graduated” to heroin. As with most addicts, as his opiate habit developed his life began to unravel. Family, friends and career became less and less important. Maintaining his expensive addiction became the most important priority each day. But when a winter blizzard came one December and “his guy” stopped returning his phone calls, Sebastian knew another kind of storm was heading his way. Withdrawal. He suffered in bed for a few days before his dealer finally returned his calls and delivered the goods. But this was the final turning point. After all he had gone through, Sebastian knew things couldn’t continue like this. So he made arrangements to visit a Suboxone-prescribing doctor, and very shortly thereafter, he was finally on the long road to recovery.
But while being treated with Suboxone, Sebastian had some anxieties and a lot of questions. “How long should I really be on this stuff? Should I try to taper off or not? And if so, how do you do it so as to minimize any discomfort? What other things should I be doing to aid in my recovery?” He looked to the Internet for answers, but what he found was a lot of contradictory information, posts from people claiming that “this stuff is even worse than what I was on before!”, and even disagreement among doctors and other health professionals with regard to Suboxone treatment protocols. Sebastian suspected that if he found all this confusing, there were probably many others in the same boat.
And so, he set out to investigate all of this, and to write a book that explained his findings in clear and simple terms. Sebastian spoke with various doctors, Suboxone patients and therapists, and synthesized their views and opinions, along with his own experiences, into a book of tips and suggestions that would help doctors and patients best approach buprenorphine treatment.
Sebastian begins with his own compelling story, where he details the life journey that ultimately led to drug addiction. He then presents several suggestions and tips that cover a wide range of questions he knew Suboxone patients had. The book covers a variety of topics, such as how to best select a doctor, how to approach counseling (and whether you really need counseling), how to taper off the medication with minimal discomfort (and whether you even should taper off the medication), resources that may help with paying for treatment, and a variety of “lifestyle hacks” Sebastian found to be useful while being treated. Sebastian lays all of this out clearly, and provides a positive and motivating read that will help patients understand that treatment with buprenorphine need not be a scary and uncertain thing. On the contrary, it can be a constructive part of recovery from opiate addiction. As he put it, “This is the book I wish I had when I began buprenorphine treatment.”
DMSO is a natural chemical compound derived from trees as a by-product from paper manufacturing. DMSO has been called a new medical principle and a true wonder drug. It has proven effective, either by itself or in combination with other products in the treatment of nearly every ailment known.
There has been much controversy about DMSO over the last 50 years. It is one of the most studied medical products ever. Thousands of scientific articles have been written about DMSO. When used properly it is one of the safest products know. It is also very cheap to produce.
This book provides the documentation needed to show that DMSO is probably the most important product ever for the relief of human suffering.
******Archie is quite clearly a leading authorithy on DMSO. He has extensive knowledge and experience regarding the clinical benefits of DMSO treatment. For decades, Archie has studied and worked with DMSO. He understands the safety, utility and efficaciousness of DMSO. I highly recommend this book for anyone interested in health, especially for those who want to learn more about non toxic medical therapies. For individuals with certain health ailments, DMSO could prove quite benefical. -Daniel Junck, MD
Kratom and Other Mitragynines: The Chemistry and Pharmacology of Opioids from a Non-Opium Sourcepresents an introduction to the chemical and biological properties of alkaloids isolated from M. speciosa as well as their synthetic analogs. The book covers various topics including phytochemistry, medicinal chemistry, and pharmacology. Current research, analgesic effects, and addiction potential are also discussed. As the first extensive text on the basic science and clinical use of Kratom, the book provides readers with a concise yet comprehensive introduction to nature’s "other opioid."
Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.
And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.
Every card includes:Generic and common name Class Dosage Forms Approved Dose and Indications Off-Label Use Contraindications Adverse Reactions Drug Interactions Monitoring Parameters Medication Safety Issues and Black Box Warnings Clinical pearls that help guide patient care Strong focus on patient safety
This edition is enhanced by 11 new cards, key adult and pediatric immunization vaccines, and MP3 audio download with detailed discussion of each drug.
All these problems have been shielded from public scrutiny because they're too complex to capture in a sound bite. But Ben Goldacre shows that the true scale of this murderous disaster fully reveals itself only when the details are untangled. He believes we should all be able to understand precisely how data manipulation works and how research misconduct in the medical industry affects us on a global scale.
With Goldacre's characteristic flair and a forensic attention to detail, Bad Pharma reveals a shockingly broken system and calls for regulation. This is the pharmaceutical industry as it has never been seen before.
Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses.
Presenting theoretical knowledge and applied practical considerations, this title
provides an in-depth discussion of recent advances in sterilization
identifies obstacles that may be encountered at any stage of the validation program, and suggests the newest and most advanced solutions
explores distinctive and specific process steps, and identifies critical process control points to reach acceptable results
blends the use of theoretical knowledge with recent technological advancements to achieve applied practical solutions
Sampling of Populations, Fourth Edition continues to serve as an all-inclusive resource on the basic and most current practices in population sampling. Maintaining the clear and accessible style of the previous edition, this book outlines the essential statistical methodsfor survey design and analysis, while also exploring techniques that have developed over the past decade.
The Fourth Edition successfully guides the reader through the basic concepts and procedures that accompany real-world sample surveys, such as sampling designs, problems of missing data, statistical analysis of multistage sampling data, and nonresponse and poststratification adjustment procedures. Rather than employ a heavily mathematical approach, the authors present illustrative examples that demonstrate the rationale behind common steps in the sampling process, from creating effective surveys to analyzing collected data. Along with established methods, modern topics are treated through the book's new features, which include:A new chapter on telephone sampling, with coverage of declining response rates, the creation of "do not call" lists, and the growing use of cellular phones A new chapter on sample weighting that focuses on adjustments to weight for nonresponse, frame deficiencies, and the effects of estimator instability An updated discussion of sample survey data analysis that includes analytic procedures for estimation and hypothesis testing A new section on Chromy's widely used method of taking probability proportional to size samples with minimum replacement of primary sampling units An expanded index with references on the latest research in the field
All of the book's examples and exercises can be easily worked out using various software packages including SAS, STATA, and SUDAAN, and an extensive FTP site contains additional data sets. With its comprehensive presentation and wealth of relevant examples, Sampling of Populations, Fourth Edition is an ideal book for courses on survey sampling at the upper-undergraduate and graduate levels. It is also a valuable reference for practicing statisticians who would like to refresh their knowledge of sampling techniques.
These may not sound like typical questions for an econo-mist to ask. But Steven D. Levitt is not a typical economist. He is a much-heralded scholar who studies the riddles of everyday life—from cheating and crime to sports and child-rearing—and whose conclusions turn conventional wisdom on its head.
Freakonomics is a groundbreaking collaboration between Levitt and Stephen J. Dubner, an award-winning author and journalist. They usually begin with a mountain of data and a simple question. Some of these questions concern life-and-death issues; others have an admittedly freakish quality. Thus the new field of study contained in this book: freakonomics.
Through forceful storytelling and wry insight, Levitt and Dubner show that economics is, at root, the study of incentives—how people get what they want, or need, especially when other people want or need the same thing. In Freakonomics, they explore the hidden side of . . . well, everything. The inner workings of a crack gang. The truth about real-estate agents. The myths of campaign finance. The telltale marks of a cheating schoolteacher. The secrets of the Klu Klux Klan.
What unites all these stories is a belief that the modern world, despite a great deal of complexity and downright deceit, is not impenetrable, is not unknowable, and—if the right questions are asked—is even more intriguing than we think. All it takes is a new way of looking.
Freakonomics establishes this unconventional premise: If morality represents how we would like the world to work, then economics represents how it actually does work. It is true that readers of this book will be armed with enough riddles and stories to last a thousand cocktail parties. But Freakonomics can provide more than that. It will literally redefine the way we view the modern world.
Bonus material added to the revised and expanded 2006 editionThe original New York Times Magazine article about Steven D. Levitt by Stephen J. Dubner, which led to the creation of this book.Seven “Freakonomics” columns written for the New York Times Magazine, published between August 2005 and April 2006.Selected entries from the Freakonomics blog, posted between April 2005 and May 2006 at http://www.freakonomics.com/blog/.
Includes New and Updated Material
Now in its second edition, this work is the culmination of research and discussions with technical experts, as well as USP and FDA representatives on various topics of interest to the pharmaceutical microbiologist and those responsible for the microbial quality of products, materials, equipment, and manufacturing facilities. New in this edition is an entire chapter dedicated to the topic of biofilms and their impact on pharmaceutical and biopharmaceutical operations. The subject of rapid methods in microbiology has been expanded and includes a discussion on the validation of alternative microbiological methods and a case study on microbial identification in support of a product contamination investigation.
Substantially updated and revised, this book assists readers in understanding the fundamental issues associated with pharmaceutical microbiology and provides them with tools to create effective microbial contamination control and microbial testing programs for the areas under their responsibility.
Developed for use at the point of care, Pharmacotherapy Bedside Guide helps you decide which pharmacotherapy to employ in specific clinical situations. Comprised exclusively of quick-hit tables and algorithms, this carryanywhere companion tells you what treatment the evidence suggests for each illness or disorder. It also details essential drug information, such as benefits, risks, adverse reactions, dosage, interactions with other drugs, and responses. Conveniently organized by specialty and disorder rather than drug, Pharmacotherapy Bedside Guide will prove invaluable when treating patients.
Here, Dr. Mann, a nationally recognized hypertension specialist, identifies the drugs most likely to have side effects, and those that can be used in their place. He describes the shortcomings of some of the new drugs, while also introducing readers to some excellent old drugs that are woefully underused as a result of the publicity blitz surrounding the new, expensive ones. He emphasizes the importance of matching the medication and dosage to the individual who will be taking them, and presents the overlooked clues that can tell us who should be on which drug (even an excellent drug can be the wrong one if it is given to the wrong person or in the wrong dose). Hypertension and You is directed at the more than 50 million Americans (including a majority of people over the age of 60) who are taking blood pressure medication. Many patients suspect they might be on the wrong medication, but don’t know enough to be sure. This book shows how medications can be prescribed more wisely to achieve better results and gives patients the knowledge they need to capably discuss their medications with their health care providers.
Hypertension and You provides many ideas and approaches that will be new to readers, and also to many physicians, and which no other book offers. It’s the first book to make the case that something is terribly wrong with how doctors are prescribing drugs for this condition. It provides readers with better knowledge of the available medications, empowering them to work with their physician to get onto the medications that are right for them.
"These cards offer concise yet detailed case studies for students to review current pharmacotherapeutic options for many of the commonly encountered disease states....Students might find these cards to be a very helpful in addition to their therapeutics courses to help them retain knowledge through the use of real-life clinical scenarios. 3 Stars."--Doody's Review Service
These 238 Q&A cards provide a complete review of pharmacotherapeutic concepts for the major disease states most often encountered in practiceEmphasizes evidence-based therapeutic decision making and drug therapy monitoring Each card features a case and therapeutic question Key facts are included for the drug or drug class that correctly answers the question Case Notes explain the answer and include clinical pearls about use of the drug, management of the disease, and dosing
Miracle Medicines goes behind the scenes of the pharmaceutical industry and into the high-security laboratories to tell the stories of the men and women---chemists, physiologists, medical and clinical researchers, engineers---who have chosen to toil for years in the lab in order to transform scientific theories into new lifesaving medicines.
You’ll witness the day-to-day labors, victories and defeats of the dedicated professionals who are waging a war against the diseases that still plague mankind. From the confines of their laboratories, these pharmaceutical adventurers explore unknown territories in health and science.
Miracle Medicines reveals what really happens during the long and uncertain journey that each new drug and its creators must endure from theory, to research, to testing and, finally, FDA approval and delivery to the public. It’s a very human story within the context of fascinating scientific innovation.
Through first hand interviews you’ll also meet the patients who benefit from these manmade miracles and learn how, within their bloodstreams, an ongoing battle is raging. The drugs profiled are:Advair: GlaxoSmithKline’s revolutionary asthma medication, the first packaged as both a control and emergency drug.Gleevec: The Novartis’ chronic myeloid leukemia treatment born from decades of medical research in a field of study that was once considered hopeless.Humalog: Eli Lilly’s reinvention of insulin to control diabetes has been described as being better than natureLipitor: Pfizer’s miracle antidote for high cholesterol that was nearly lost to the pharmaceutical vaults and has since become the world’s top-selling medicine.Norvir: Abbott’s contribution to the fight against HIV that nearly erases all traces of the disease from the bloodstream and prolongs the life of patients.Remicade: Created for the treatment of Crohn’s disease, rheumatoid arthritis and other Immune Mediated Inflammatory Diseases, Johnson & Johnson’s revolutionary biomedicine was developed from technology that once was only found in science fiction.Seroquel: AstraZeneca’s treatment for both schizophrenia and bipolar mania that has given millions of psychiatrics a new lease on life.
This compelling and truth-revealing book will forever change the way you view the medicines in your medicine cabinet, and the people who create them.
The authors offer a basic introduction to pharmacological concepts, embedded in specific conditions, through case studies and self-assessment questions. By utilising a case study approach, they enable the reader to link pharmacological concepts with clinical practice.
Many of the conditions presented will be seen across all healthcare settings. In addition, the comprehensive glossary and list of abbreviations will enable students to understand some of the more technical terms used in the British National Formulary (BNF) and other prescribing sources.
Reading this book, and carrying out the numerous self-assessment activities, will give the reader an appreciation of the value of having a sound pharmacological knowledge base in order to deliver safe practice, effective prescribing and improved patient care.
How the body affects drugs
How drugs affect the body
Types of adverse drug reactions and interactions
Understanding and using the British National Formulary
Chronic obstructive pulmonary disease
Incontinence in adults
Mental health problems
Complex health needs and polypharmacy
The challenges of non-medical prescribing
CD-ROM performs 30 statistical tests
Don't be afraid of biostatistics anymore! Primer of Biostatistics,7th Edition demystifies this challenging topic in an interesting and enjoyable manner that assumes no prior knowledge of the subject. Faster than you thought possible, you'll understand test selection and be able to evaluate biomedical statistics critically, knowledgeably, and confidently.
With Primer of Biostatistics, you’ll start with the basics, including analysis of variance and the t test, then advance to multiple comparison testing, contingency tables, regression, and more. Illustrative examples and challenging problems, culled from the recent biomedical literature, highlight the discussions throughout and help to foster a more intuitive approach to biostatistics.
The companion CD-ROM contains everything you need to run thirty statistical tests of your own data. Review questions and summaries in each chapter facilitate the learning process and help you gauge your comprehension. By combining whimsical studies of Martians and other planetary residents with actual papers from the biomedical literature, the author makes the subject fun and engaging.
Coverage includes:How to summarize data How to test for differences between groups The t test How to analyze rates and proportions What does “not significant” really mean? Confidence intervals How to test for trends Experiments when each subject receives more than one treatment Alternatives to analysis of variance and the t test based on ranks How to analyze survival data
* Easy-to-follow format incorporates medical examples, step-by-step methods, and check yourself exercises
* Two-part design features course material and a professional reference section
* Chapter summaries provide a review of formulas, method algorithms, and check lists
* Companion site links to statistical databases that can be downloaded and used to perform the exercises from the book and practice statistical methods
New in this Edition:
* New chapters on: multifactor tests on means of continuous data, equivalence testing, and advanced methods
* New topics include: trial randomization, treatment ethics in medical research, imputation of missing data, and making evidence-based medical decisions
* Updated database coverage and additional exercises
* Expanded coverage of numbers needed to treat and to benefit, and regression analysis including stepwise regression and Cox regression
Thorough discussion on required sample size
Water Insolubility is the Primary Culprit in over 40% of New Drug Development Failures
The most comprehensive resource on the topic, this second edition of Water Insoluble Drug Formulation brings together a distinguished team of experts to provide the scientific background and step-by-step guidance needed to deal with solubility issues in drug development. Twenty-three chapters systematically describe solubility properties and their impact on formulation, from theory to industrial practice. With detailed discussion on how these properties contribute to solubilization and dissolution, the text also features six brand new chapters on water-insoluble drugs, exploring regulatory aspects, pharmacokinetic behavior, early phase formulation strategies, lipid based systems for oral delivery, modified release of insoluble drugs, and scalable manufacturing aspects. The book includes more than 15 water-insoluble drug delivery systems or technologies, illustrated with case studies featuring oral and parenteral applications. Highlighting the most current information and data available, this seminal volume reflects the significant progress that has been made in nearly all aspects of this field.
Side Effects tells the tale of a gutsy assistant attorney general who, along with an unlikely whistle-blower at an Ivy League university, uncovered evidence of deception behind one of the most successful drug campaigns in history. Paxil was the world's bestselling antidepressant in 2002. Pediatric prescriptions soared, even though there was no proof that the drug performed any better than sugar pills in treating children and adolescents, and the real risks the drugs posed were withheld from the public. The New York State Attorney General's office brought an unprecedented lawsuit against giant manufacturer GlaxoSmithKline, the maker of Paxil, for consumer fraud. The successful suit launched a tidal wave of protest that changed the way drugs are tested, sold, and marketed in this country.
With meticulous research, Alison Bass shows us the underbelly of the pharmaceutical industry. She lays bare the unhealthy ties between the medical establishment, big pharma, and the FDA—relationships that place vulnerable children and adults at risk every day.
Pharmacotherapy Handbook provides the critical information you need to make drug therapy decisions for more than 140 diseases and disorders commonly encountered in a clinical setting. Featuring a convenient alphabetized presentation, this handy guide utilizes text, tables, figures, and treatment algorithms to make important drug data readily accessible and easily understood.
Features:Consistent chapter organization includes: Disease state definition Concise review of relevant pathophysiology Clinical presentation Diagnosis Goals of treatment Treatment Monitoring Six appendices, including "Allergic and Pseudoallergic Drug Reactions" and "Geriatrics" The ideal companion to Pharmacotherapy: A Pathophysiologic Approach, Ninth Edition by Joseph DiPiro, et al
—Robert Harrington, Professor of Medicine, Director, Duke Clinical Research Institute, Durham, North Carolina, USA
The Duke Clinical Research Institute (DCRI) is one of the world's leading academic clinical research organizations; its mission is to develop and share knowledge that improves the care of patients around the world through innovative clinical research. This concise handbook provides a practical "nuts and bolts" approach to the process of conducting clinical trials, identifying methods and techniques that can be replicated at other institutions and medical practices.
Designed for investigators, research coordinators, CRO personnel, students, and others who have a desire to learn about clinical trials, this manual begins with an overview of the historical framework of clinical research, and leads the reader through a discussion of safety concerns and resulting regulations. Topics include Good Clinical Practice, informed consent, management of subject safety and data, as well as monitoring and reporting adverse events.
Updated to reflect recent regulatory and clinical developments, the manual reviews the conduct of clinical trials research in an increasingly global context. This new edition has been further expanded to include:In-depth information on conducting clinical trials of medical devices and biologics The role and responsibilities of Institutional Review Boards, and Recent developments regarding subject privacy concerns and regulations.
Ethical documents such as the Belmont Report and the Declaration of Helsinki are reviewed in relation to all aspects of clinical research, with a discussion of how researchers should apply the principles outlined in these important documents. This graphically appealing and eminently readable manual also provides sample forms and worksheets to facilitate data management and regulatory record retention; these can be modified and adapted for use at investigative sites.