Modern Analysis of Customer Surveys. with Applications using R

A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.

H andbook and reference guide for students and practitioners of statistical regression-based analyses in R   Handbook of Regression Analysis  with Applications in R, Second Edition  is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors’ thorough treatment of “classical” regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data.  The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include:  Regularization methods Smoothing methods Tree-based methods In the new edition of the  Handbook , the data analyst’s toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website.  Of interest to undergraduate and graduate students taking courses in statistics and regression, the  Handbook of Regression Analysis  will also be invaluable to practicing data scientists and statisticians.

Edited by two very well-known and respected scientists in the field, this excellent practical guide is the first to cover the fundamentals and a wide range of applications, as well as showing readers how to efficiently use this increasingly important technique. From the contents: * The Isotopic Composition of the Elements * Single-Collector ICP-MS * Multi-Collector ICP-MS * Advances in Laser Ablation – Multi-Collector ICP-MS * Correction for Instrumental Mass Discrimination in Isotope Ratio Determination with Multi-Collector ICP-MS * Reference Materials in Isotopic Analysis * Quality Control in Isotope Ratio Applications * Determination of Trace Elements and Elemental Species Using Isotope Dilution ICP-MS * Geochronological Dating * Application of Multi-Collector ICP-MS to Isotopic Analysis in Cosmochemistry * Establishing the Basis for Using Stable Isotope Ratios of Metals as Paleoredox Proxies * Isotopes as Tracers of Elements Across the Geosphere-Biosphere Interface * Archaeometric Applications * Forensics Applications * Nuclear Applications * The Use of Stable Isotope Techniques for Studying Mineral and Trace Element Metabolism in Humans * Isotopic Analysis via Multi-Collector ICP-MS in Elemental Speciation A must-have for newcomers as well as established scientists seeking an overview of isotopic analysis via ICP-MS.

An accessible introduction to performing meta-analysis across various areas of research The practice of meta-analysis allows researchers to obtain findings from various studies and compile them to verify and form one overall conclusion. Statistical Meta-Analysis with Applications presents the necessary statistical methodologies that allow readers to tackle the four main stages of meta-analysis: problem formulation, data collection, data evaluation, and data analysis and interpretation. Combining the authors' expertise on the topic with a wealth of up-to-date information, this book successfully introduces the essential statistical practices for making thorough and accurate discoveries across a wide array of diverse fields, such as business, public health, biostatistics, and environmental studies. Two main types of statistical analysis serve as the foundation of the methods and techniques: combining tests of effect size and combining estimates of effect size. Additional topics covered include: Meta-analysis regression procedures Multiple-endpoint and multiple-treatment studies The Bayesian approach to meta-analysis Publication bias Vote counting procedures Methods for combining individual tests and combining individual estimates Using meta-analysis to analyze binary and ordinal categorical data Numerous worked-out examples in each chapter provide the reader with a step-by-step understanding of the presented methods. All exercises can be computed using the R and SAS software packages, which are both available via the book's related Web site. Extensive references are also included, outlining additional sources for further study. Requiring only a working knowledge of statistics, Statistical Meta-Analysis with Applications is a valuable supplement for courses in biostatistics, business, public health, and social research at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians working in industry, academia, and government.

A comprehensive introduction to social network analysis that hones in on basic centrality measures, social links, subgroup analysis, data sources, and more Written by military, industry, and business professionals, this book introduces readers to social network analysis, the new and emerging topic that has recently become of significant use for industry, management, law enforcement, and military practitioners for identifying both vulnerabilities and opportunities in collaborative networked organizations. Focusing on models and methods for the analysis of organizational risk, Social Network Analysis with Applications provides easily accessible, yet comprehensive coverage of network basics, centrality measures, social link theory, subgroup analysis, relational algebra, data sources, and more. Examples of mathematical calculations and formulas for social network measures are also included. Along with practice problems and exercises, this easily accessible book covers: The basic concepts of networks, nodes, links, adjacency matrices, and graphs Mathematical calculations and exercises for centrality, the basic measures of degree, betweenness, closeness, and eigenvector centralities Graph-level measures, with a special focus on both the visual and numerical analysis of networks Matrix algebra, outlining basic concepts such as matrix addition, subtraction, multiplication, and transpose and inverse calculations in linear algebra that are useful for developing networks from relational data Meta-networks and relational algebra, social links, diffusion through networks, subgroup analysis, and more An excellent resource for practitioners in industry, management, law enforcement, and military intelligence who wish to learn and apply social network analysis to their respective fields, Social Network Analysis with Applications is also an ideal text for upper-level undergraduate and graduate level courses and workshops on the subject.

This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include: • Broad appeal–the authors target their material to researchers in several levels, ensuring that the basics are always covered. • First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology. • Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users.

This volume contains papers presented at The 15th International Conference on the Texture of Materials from June 1-5th, 2008 in Pittsburgh, PA. Chapters include: Thin Films Texture at Non-Ambient Conditions Novel Texture Measurement Techniques Including 3D Complex Oxides Interface Textures Recrystallization Texture Biomaterials Texture Effects on Damage Accumulation Digital Microstructures View information on Materials Processing and Texture: Ceramic Transactions, Volume 200.

Design and Analysis of Composite Structures enables graduate students and engineers to generate meaningful and robust designs of complex composite structures. Combining analysis and design methods for structural components, the book begins with simple topics such as skins and stiffeners and progresses through to entire components of fuselages and wings. Starting with basic mathematical derivation followed by simplifications used in real-world design, Design and Analysis of Composite Structures presents the level of accuracy and range of applicability of each method. Examples taken from actual applications are worked out in detail to show how the concepts are applied, solving the same design problem with different methods based on different drivers (e.g. cost or weight) to show how the final configuration changes as the requirements and approach change. Provides a toolkit of analysis and design methods to most situations encountered in practice, as well as analytical frameworks and the means to solving them for tackling less frequent problems. Presents solutions applicable to optimization schemes without having to run finite element models at each iteration, speeding up the design process and allowing examination of several more alternatives than traditional approaches. Includes guidelines showing how decisions based on manufacturing considerations affect weight and how weight optimization may adversely affect the cost. Accompanied by a website at www.wiley.com/go/kassapoglou hosting lecture slides and solutions to the exercises for instructors.

A much-needed guide on how to use numerical methods to solve practical engineering problems Bridging the gap between mathematics and engineering, Numerical Analysis with Applications in Mechanics and Engineering arms readers with powerful tools for solving real-world problems in mechanics, physics, and civil and mechanical engineering. Unlike most books on numerical analysis, this outstanding work links theory and application, explains the mathematics in simple engineering terms, and clearly demonstrates how to use numerical methods to obtain solutions and interpret results. Each chapter is devoted to a unique analytical methodology, including a detailed theoretical presentation and emphasis on practical computation. Ample numerical examples and applications round out the discussion, illustrating how to work out specific problems of mechanics, physics, or engineering. Readers will learn the core purpose of each technique, develop hands-on problem-solving skills, and get a complete picture of the studied phenomenon. Coverage includes: How to deal with errors in numerical analysis Approaches for solving problems in linear and nonlinear systems Methods of interpolation and approximation of functions Formulas and calculations for numerical differentiation and integration Integration of ordinary and partial differential equations Optimization methods and solutions for programming problems Numerical Analysis with Applications in Mechanics and Engineering is a one-of-a-kind guide for engineers using mathematical models and methods, as well as for physicists and mathematicians interested in engineering problems.