A User’s Guide to Network Analysis in R

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Author: Douglas Luke

Publisher: Springer

ISBN: 3319238833

Category: Mathematics

Page: 238

View: 8891

Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.

Network Analysis and Visualization in R

Quick Start Guide

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Author: Alboukadel Kassambara

Publisher: STHDA

ISBN: 1981179674

Category:

Page: 39

View: 4541

Social network analysis is used to investigate the inter-relationship between entities. Examples of network structures, include: social media networks, friendship networks and collaboration networks. This book provides a quick start guide to network analysis and visualization in R. You'll learn, how to: - Create static and interactive network graphs using modern R packages. - Change the layout of network graphs. - Detect important or central entities in a network graph. - Detect community (or cluster) in a network.

Modeling Techniques in Predictive Analytics with Python and R

A Guide to Data Science

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Author: Thomas W. Miller

Publisher: FT Press

ISBN: 013389214X

Category: Computers

Page: 448

View: 2396

Master predictive analytics, from start to finish Start with strategy and management Master methods and build models Transform your models into highly-effective code—in both Python and R This one-of-a-kind book will help you use predictive analytics, Python, and R to solve real business problems and drive real competitive advantage. You’ll master predictive analytics through realistic case studies, intuitive data visualizations, and up-to-date code for both Python and R—not complex math. Step by step, you’ll walk through defining problems, identifying data, crafting and optimizing models, writing effective Python and R code, interpreting results, and more. Each chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work—and maximize their value. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, addresses everything you need to succeed: strategy and management, methods and models, and technology and code. If you’re new to predictive analytics, you’ll gain a strong foundation for achieving accurate, actionable results. If you’re already working in the field, you’ll master powerful new skills. If you’re familiar with either Python or R, you’ll discover how these languages complement each other, enabling you to do even more. All data sets, extensive Python and R code, and additional examples available for download at http://www.ftpress.com/miller/ Python and R offer immense power in predictive analytics, data science, and big data. This book will help you leverage that power to solve real business problems, and drive real competitive advantage. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, illuminating each technique with carefully explained code for the latest versions of Python and R. If you’re new to predictive analytics, Miller gives you a strong foundation for achieving accurate, actionable results. If you’re already a modeler, programmer, or manager, you’ll learn crucial skills you don’t already have. Using Python and R, Miller addresses multiple business challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic code that delivers actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. Appendices include five complete case studies, and a detailed primer on modern data science methods. Use Python and R to gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Theorie nichtlinearer Netzwerke

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Author: Wolfgang Mathis

Publisher: Springer-Verlag

ISBN: 364283227X

Category: Technology & Engineering

Page: 401

View: 4623

Das Lehrbuch behandelt die nichtlineare Netzwerktheorie, ausgehend von einem geometrischen Standpunkt. Die zur Geometrisierung der Theorie verwendeten mathematischen Konzepte werden in einleitenden Kapiteln dargestellt. Der Leser findet eine präzise Beschreibung in einer Sprache, die die Theorie transparent und leicht merkbar macht. Nach Definition von System- und Netzwerkbegriff wird auf die Modellbildung eingegangen und das Modell der Realisierung vergleichend gegenüberstellt. Neben klassischen Beiträgen zur zeitvarianten Theorie findet man auch störungstheoretische Methoden. Das Buch stellt die Theorie nichtlinearer Netzwerke in neuer Konzeption dar, die den Leser an die neuere Entwicklung heranführt. Zahlreiche Beispiele illustrieren das primär für Elektrotechnik-Studenten höherer Semester an technischen Hochschulen bestimmte Werk.

Mastering Gephi Network Visualization

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Author: Ken Cherven

Publisher: Packt Publishing Ltd

ISBN: 1783987359

Category: Computers

Page: 378

View: 7346

This book is intended for anyone interested in advanced network analysis. If you wish to master the skills of analyzing and presenting network graphs effectively, then this is the book for you. No coding experience is required to use this book, although some familiarity with the Gephi user interface will be helpful.

Using R for Numerical Analysis in Science and Engineering

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Author: Victor A. Bloomfield

Publisher: CRC Press

ISBN: 1439884498

Category: Mathematics

Page: 359

View: 2233

Instead of presenting the standard theoretical treatments that underlie the various numerical methods used by scientists and engineers, Using R for Numerical Analysis in Science and Engineering shows how to use R and its add-on packages to obtain numerical solutions to the complex mathematical problems commonly faced by scientists and engineers. This practical guide to the capabilities of R demonstrates Monte Carlo, stochastic, deterministic, and other numerical methods through an abundance of worked examples and code, covering the solution of systems of linear algebraic equations and nonlinear equations as well as ordinary differential equations and partial differential equations. It not only shows how to use R’s powerful graphic tools to construct the types of plots most useful in scientific and engineering work, but also: Explains how to statistically analyze and fit data to linear and nonlinear models Explores numerical differentiation, integration, and optimization Describes how to find eigenvalues and eigenfunctions Discusses interpolation and curve fitting Considers the analysis of time series Using R for Numerical Analysis in Science and Engineering provides a solid introduction to the most useful numerical methods for scientific and engineering data analysis using R.

Social Network Analysis

A Handbook

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Author: John Scott

Publisher: SAGE

ISBN: 0761963383

Category: Social Science

Page: 208

View: 7864

The revised and updated edition of this bestselling text provides an accessible introduction to the theory and practice of network analysis in the social sciences. It gives a clear and authoritative guide to the general framework of network analysis, explaining the basic concepts, technical measures and reviewing the available computer programs. The book outlines both the theoretical basis of network analysis and the key techniques for using it as a research tool. Building upon definitions of points, lines and paths, John Scott demonstrates their use in clarifying such measures as density, fragmentation and centralization. He identifies the various cliques, components and circles into which networks are formed, and outlines

Qualitative Comparative Analysis with R

A User’s Guide

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Author: Alrik Thiem,Adrian Dusa

Publisher: Springer Science & Business Media

ISBN: 1461445841

Category: Political Science

Page: 99

View: 8766

Social science theory often builds on sets and their relations. Correlation-based methods of scientific enquiry, however, use linear algebra and are unsuited to analyzing set relations. The development of Qualitative Comparative Analysis (QCA) by Charles Ragin has given social scientists a formal tool for identifying set-theoretic connections based on Boolean algebra. As a result, interest in this method has markedly risen among social scientists in recent years. This book offers the first complete introduction on how to perform QCA in the R software environment for statistical computing and graphics with the QCA package. Developed as a comprehensive solution, QCA provides an unprecedented scope of functionality for analyzing crisp, multi-value and fuzzy sets. The reader is not required to have knowledge of R, but the book assumes an understanding of the fundamentals of QCA. Using examples from published work, the authors demonstrate how to make the most of QCA’s wide-ranging capabilities for the reader’s own purposes. Although mainly written for political scientists, this book is also of interest to scholars from other disciplines in the social sciences such as sociology, business, management, organization, anthropology, education and health.

Users Guide to Physical Modelling and Experimentation

Experience of the HYDRALAB Network

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Author: Lynne E. Frostick,Stuart J. McLelland,T.G. Mercer

Publisher: CRC Press

ISBN: 1439870519

Category: Technology & Engineering

Page: 272

View: 980

A Users Guide to Hydraulic Modelling and Experimentation provides a systematic, comprehensive summary of the progress made through HYDRALAB III . The book combines the expertise of many of the leading hydraulic experimentalists in Europe and identifies current best practice for carrying out state-of-the-art, modern laboratory investigations. In addition it gives an inventory and reviews recent advances in instrumentation and equipment that drive present and new developments in the subject. The Guide concentrates on four core areas – waves, breakwaters, sediments and the relatively-new (but rapidly-developing) cross-disciplinary area of hydrodynamics/ecology. Progress made through the ‘CoMIBBS’ component of HYDRALAB III provides the material for a chapter focussed on guidance, principles and practice for composite modelling. There is detailed consideration of scaling and the degree of relevance of laboratory/physical modelling approaches for specific contexts included in each of the individual chapters. The Guide includes outputs from the workshops and several of the innovative transnational access projects that have been supported within HYDRALAB III, as well as the focussed joint research activities SANDS and CoMIBBS. Its primary purpose is to serve as a shared resource to disseminate the outstanding advances achieved within HYDRALAB III but, even more than this, it is a tribute to the human and institutional collaborations that led to and sustained the research advances, the human relationships that were strengthened and initiated through joint participation in the Programme, and the training opportunities that participation provided to the many young researchers engaged in the projects.

Cyber Security for Educational Leaders

A Guide to Understanding and Implementing Technology Policies

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Author: Richard Phillips,Rayton R. Sianjina

Publisher: Routledge

ISBN: 1136217347

Category: Education

Page: 176

View: 6225

As leaders are increasingly implementing technologies into their districts and schools, they need to understand the implications and risks of doing so. Cyber Security for Educational Leaders is a much-needed text on developing, integrating, and understanding technology policies that govern schools and districts. Based on research and best practices, this book discusses the threats associated with technology use and policies and arms aspiring and practicing leaders with the necessary tools to protect their schools and to avoid litigation. Special Features: A Cyber Risk Assessment Checklist and Questionnaire helps leaders measure levels of risk in eight vital areas of technology usage. Case vignettes illuminate issues real leaders have encountered and end-of-chapter questions and activities help readers make connections to their own practice. Chapter alignment with the ELCC standards. An entire chapter on Copyright and Fair Use that prepares leaders for today’s online world. A Companion Website with additional activities, assessment rubrics, learning objectives, and PowerPoint slides.

Information Rules

A Strategic Guide to the Network Economy

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Author: Carl Shapiro,Hal R. Varian

Publisher: Harvard Business Press

ISBN: 1422154629

Category: Business & Economics

Page: 352

View: 6310

In Information Rules, authors Shapiro and Varian reveal that many classic economic concepts can provide the insight and understanding necessary to succeed in the information age. They argue that if managers seriously want to develop effective strategies for competing in the new economy, they must understand the fundamental economics of information technology. Whether information takes the form of software code or recorded music, is published in a book or magazine, or even posted on a website, managers must know how to evaluate the consequences of pricing, protecting, and planning new versions of information products, services, and systems. The first book to distill the economics of information and networks into practical business strategies, Information Rules is a guide to the winning moves that can help business leaders navigate successfully through the tough decisions of the information economy.

Introduction to Data Analysis and Graphical Presentation in Biostatistics with R

Statistics in the Large

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Author: Thomas W. MacFarland

Publisher: Springer Science & Business Media

ISBN: 3319025325

Category: Medical

Page: 167

View: 2409

Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include tools that are critical to dealing with missing data, which is a pressing scientific issue for those engaged in biostatistics. Readers will be equipped to run analyses and make graphical presentations based on the sample dataset and their own data. The hands-on approach will benefit students and ensure the accessibility of this book for readers with a basic understanding of R. Topics include: an introduction to Biostatistics and R, data exploration, descriptive statistics and measures of central tendency, t-Test for independent samples, t-Test for matched pairs, ANOVA, correlation and linear regression, and advice for future work.

Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide

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Author: Agency for Health Care Research and Quality (U.S.)

Publisher: Government Printing Office

ISBN: 1587634236

Category: Medical

Page: 204

View: 937

This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)

Neuromuscular Ultrasound E-Book

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Author: Francis Walker,Michael S. Cartwright

Publisher: Elsevier Health Sciences

ISBN: 1437737765

Category: Medical

Page: 208

View: 967

Neuromuscular Ultrasound demonstrates the use of ultrasound as an alternative to electrodiagnosis in the evaluation of neuromuscular disorders through detailed descriptions and clear illustrations. Drs. Francis Walker and Michael S. Cartwright discuss techniques for visualizing muscles and nerves without painful testing for better patient compliance and more efficient diagnosis. Color illustrations, pearls for the clinician, and ultrasound videos online at www.expertconsult.com, ensure that you’ll be able to apply this technology effectively in your practice. Access the fully searchable text online at www.expertconsult.com, along with ultrasound videos that demonstrate ultrasound evaluation in real time. Diagnose and manage your patients more quickly and easily by visualizing muscles and nerves without painful testing. Master the nuances of using ultrasound through the visual instruction of clear images and illustrations. Minimize patient discomfort while maximizing optimal patient evaluation with a practical focus that covers using ultrasound as a screening tool, provides clinical pearls, and includes comparisons to electrodiagnosis. Apply the full range of ultrasound applications, including interventional uses (such as ultrasound-guided botulinum toxin and steroid injections), ultrasound of polyneuropathies (often found in diabetics), and more.

R Data Analysis Projects

Build end to end analytics systems to get deeper insights from your data

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Author: Gopi Subramanian

Publisher: Packt Publishing Ltd

ISBN: 1788620577

Category: Computers

Page: 366

View: 3433

Get valuable insights from your data by building data analysis systems from scratch with R. About This Book A handy guide to take your understanding of data analysis with R to the next level Real-world projects that focus on problems in finance, network analysis, social media, and more From data manipulation to analysis to visualization in R, this book will teach you everything you need to know about building end-to-end data analysis pipelines using R Who This Book Is For If you are looking for a book that takes you all the way through the practical application of advanced and effective analytics methodologies in R, then this is the book for you. A fundamental understanding of R and the basic concepts of data analysis is all you need to get started with this book. What You Will Learn Build end-to-end predictive analytics systems in R Build an experimental design to gather your own data and conduct analysis Build a recommender system from scratch using different approaches Use and leverage RShiny to build reactive programming applications Build systems for varied domains including market research, network analysis, social media analysis, and more Explore various R Packages such as RShiny, ggplot, recommenderlab, dplyr, and find out how to use them effectively Communicate modeling results using Shiny Dashboards Perform multi-variate time-series analysis prediction, supplemented with sensitivity analysis and risk modeling In Detail R offers a large variety of packages and libraries for fast and accurate data analysis and visualization. As a result, it's one of the most popularly used languages by data scientists and analysts, or anyone who wants to perform data analysis. This book will demonstrate how you can put to use your existing knowledge of data analysis in R to build highly efficient, end-to-end data analysis pipelines without any hassle. You'll start by building a content-based recommendation system, followed by building a project on sentiment analysis with tweets. You'll implement time-series modeling for anomaly detection, and understand cluster analysis of streaming data. You'll work through projects on performing efficient market data research, building recommendation systems, and analyzing networks accurately, all provided with easy to follow codes. With the help of these real-world projects, you'll get a better understanding of the challenges faced when building data analysis pipelines, and see how you can overcome them without compromising on the efficiency or accuracy of your systems. The book covers some popularly used R packages such as dplyr, ggplot2, RShiny, and others, and includes tips on using them effectively. By the end of this book, you'll have a better understanding of data analysis with R, and be able to put your knowledge to practical use without any hassle. Style and approach This book takes a unique, learn-as-you-do approach, as you build on your understanding of data analysis progressively with each project. This book is designed in a way that implementing each project will empower you with a unique skill set, and enable you to implement the next project more confidently.

Simulation-Based Optimization

Parametric Optimization Techniques and Reinforcement Learning

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Author: Abhijit Gosavi

Publisher: Springer Science & Business Media

ISBN: 9781402074547

Category: Science

Page: 554

View: 996

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. The book's objective is two-fold: (1) It examines the mathematical governing principles of simulation-based optimization, thereby providing the reader with the ability to model relevant real-life problems using these techniques. (2) It outlines the computational technology underlying these methods. Taken together these two aspects demonstrate that the mathematical and computational methods discussed in this book do work. Broadly speaking, the book has two parts: (1) parametric (static) optimization and (2) control (dynamic) optimization. Some of the book's special features are: *An accessible introduction to reinforcement learning and parametric-optimization techniques. *A step-by-step description of several algorithms of simulation-based optimization. *A clear and simple introduction to the methodology of neural networks. *A gentle introduction to convergence analysis of some of the methods enumerated above. *Computer programs for many algorithms of simulation-based optimization.

R and Data Mining

Examples and Case Studies

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Author: Yanchang Zhao

Publisher: Academic Press

ISBN: 012397271X

Category: Mathematics

Page: 256

View: 663

R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more. Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation. With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. Presents an introduction into using R for data mining applications, covering most popular data mining techniques Provides code examples and data so that readers can easily learn the techniques Features case studies in real-world applications to help readers apply the techniques in their work

Modeling Techniques in Predictive Analytics

Business Problems and Solutions with R, Revised and Expanded Edition

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Author: Thomas W. Miller

Publisher: FT Press

ISBN: 0133886190

Category: Computers

Page: 384

View: 3914

To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more

Endocrinology: Adult and Pediatric E-Book

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Author: J. Larry Jameson,Leslie J. De Groot

Publisher: Elsevier Health Sciences

ISBN: 032332195X

Category: Medical

Page: 2700

View: 3204

Considered the definitive source in its field for over 35 years, Endocrinology: Adult and Pediatric, has been thoroughly updated to reflect today's recent advances in adult and pediatric endocrinology. Unique perspectives from a team of trusted, world-renowned experts ensure this medical reference book remains the most highly-regarded text in the field. Make the best clinical decisions with an enhanced emphasis on evidence-based practice and expert opinions on treatment strategies. Zero in on the most relevant and useful references with the aid of a more focused, concise bibliography. Locate information quickly, while still getting the complete coverage you expect. Expanded coverage for key topics such as pediatric endocrinology and obesity mechanisms and treatment, in addition to today's hot topics in endocrinology, including endocrine disruptors, bariatric surgery, androgen deficiency, genetic causes of obesity, endocrine rhythms, and the use of tyrosine kinase inhibitors in thyroid cancer. New content addressing the latest advances in testosterone and estrogen replacement, as well as the new causes of calcium and phosphate disorders, new molecular causes of endocrine cancers, new genetic causes of reproductive disorders, and more. Updated clinical guidelines for diabetes, lipid disorders, obesity management, osteoporosis, and more, as well as essential treatment updates for the medical management of acromegaly, Cushing's Disease, hypercalcemia, and diabetes mellitus. New Key Points provide snapshots of what to expect in each chapter, or serve as a refresher of what you just read. Consult this title on your favorite e-reader.