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Analysis of Data from Randomized Controlled Trials: A Practical Guide
by Jos W.R. TwiskThis book provides a practical guide to the analysis of data from randomized controlled trials (RCT). It gives an answer to the question of how to estimate the intervention effect in an appropriate way. This problem is examined for different RCT designs, such as RCTs with one follow-up measurement, RCTs with more than one follow-up measurement, cluster RCTs, cross-over trials, stepped wedge trials, and N-of-1 trials. The statistical methods are explained in a non-mathematical way and are illustrated by extensive examples. All datasets used in the book are available for download, so readers can reanalyse the examples to gain a better understanding of the methods used. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other fields.
Analysis of Deterministic Cyclic Gene Regulatory Network Models with Delays (SpringerBriefs in Electrical and Computer Engineering)
by Mehmet Eren Ahsen Hitay Özbay Silviu-Iulian NiculescuThis brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.
Analysis of Distributional Data
by Paula BritoIn a time when increasingly larger and complex data collections are being produced, it is clear that new and adaptive forms of data representation and analysis have to be conceived and implemented. Distributional data, i.e., data where a distribution rather than a single value is recorded for each descriptor, on each unit, come into this framework. Distributional data may result from the aggregation of large amounts of open/collected/generated data, or it may be directly available in a structured or unstructured form, describing the variability of some features. This book provides models and methods for the representation, analysis, interpretation, and organization of distributional data, taking into account its specific nature, and not relying on a reduction to single values, to be conform to classical paradigms.Conceived as an edited book, gathering contributions from multiple authors, the book presents alternative representations and analysis’ methods for distributional data of different types, and in particular,-Uni- and bi-variate descriptive statistics for distributional data-Clustering and classification methodologies-Methods for the representation in low-dimensional spaces-Regression models and forecasting approaches for distribution-valued variables Furthermore, the different chapters -Feature applications to show how the proposed methods work in practice, and how results are to be interpreted, -Often provide information about available software. The methodologies presented in this book constitute cutting-edge developments for stakeholders from all domains who produce and analyse large amounts of complex data, to be analysed in the form of distributions. The book is hence of interest for companies operating not only in the area of data analytics, but also on logistics, energy and finance. It also concerns national statistical institutes and other institutions at European and international level, where microdata is aggregated to preserve confidentiality and allow for analysis at the appropriate regional level. Academics will find in the analysis of distributional data a challenging up-to-date field of research.
Analysis of Doubly Truncated Data: An Introduction (SpringerBriefs in Statistics)
by Achim Dörre Takeshi EmuraThis book introduces readers to statistical methodologies used to analyze doubly truncated data. The first book exclusively dedicated to the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods. These procedures can be used to effectively analyze continuous data, especially survival data arising in biostatistics and economics. Because truncation is a phenomenon that is often encountered in non-experimental studies, the methods presented here can be applied to many branches of science. The book provides R codes for most of the statistical methods, to help readers analyze their data. Given its scope, the book is ideally suited as a textbook for students of statistics, mathematics, econometrics, and other fields.
Analysis of Electrical Circuits with Variable Load Regime Parameters: Projective Geometry Method (Power Systems)
by A. PeninThis book introduces electric circuits with variable loads and voltage regulators. It allows to define invariant relationships for various parameters of regime and circuit sections and to prove the concepts characterizing these circuits. Generalized equivalent circuits are introduced. Projective geometry is used for the interpretation of changes of operating regime parameters. Expressions of normalized regime parameters and their changes are presented. Convenient formulas for the calculation of currents are given. Parallel voltage sources and the cascade connection of multi-port networks are described. The two-value voltage regulation characteristics of loads with limited power of voltage source is considered. The book presents the fundamentals of electric circuits and develops circuit theorems. It is useful to engineers, researchers and graduate students who are interested in the basic electric circuit theory and the regulation and monitoring of power supply systems.
Analysis of Epidemiologic Data Using R (Synthesis Lectures on Mathematics & Statistics)
by Robert HirschThis book addresses the description and analysis of occurrence data frequently encountered in epidemiological studies. With the occurrence of Covid-19, people have been exposed to the analysis and interpretation of epidemiological data. To be informed consumers of this information, people need to understand the nature and analysis of these data. Effort is made to emphasize concepts rather than mathematics. Subjects range from description of the frequencies of disease to the analysis of associations between the occurrence of disease and exposure. Those analyses begin with simple associations and work up to complex relationships that involve the control of extraneous characteristics. Analyses rely on the statistical software R, which is freeware in wide use by professional epidemiologists and other scientists.
Analysis of Failure and Survival Data (Chapman & Hall/CRC Texts in Statistical Science)
by Peter J. Smith<p>Analysis of Failure and Survival Data is an essential textbook for graduate-level students of survival analysis and reliability and a valuable reference for practitioners. It focuses on the many techniques that appear in popular software packages, including plotting product-limit survival curves, hazard plots, and probability plots in the context of censored data. <p>The author integrates S-Plus and Minitab output throughout the text, along with a variety of real data sets so readers can see how the theory and methods are applied. He also incorporates exercises in each chapter that provide valuable problem-solving experience. In addition to all of this, the book also brings to light the most recent linear regression techniques. Most importantly, it includes a definitive account of the Buckley-James method for censored linear regression, found to be the best performing method when a Cox proportional hazards method is not appropriate. <p>Applying the theories of survival analysis and reliability requires more background and experience than students typically receive at the undergraduate level. Mastering the contents of this book will help prepare students to begin performing research in survival analysis and reliability and provide seasoned practitioners with a deeper understanding of the field.</p>
Analysis of Financial Time Series
by Ruey S. TsayThis book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: Analysis and application of univariate financial time series The return series of multiple assets Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.
Analysis of Finite Difference Schemes: For Linear Partial Differential Equations with Generalized Solutions (Springer Series in Computational Mathematics #46)
by Endre Süli Boško S. JovanovićThis book develops a systematic and rigorous mathematical theory of finite difference methods for linear elliptic, parabolic and hyperbolic partial differential equations with nonsmooth solutions. Finite difference methods are a classical class of techniques for the numerical approximation of partial differential equations. Traditionally, their convergence analysis presupposes the smoothness of the coefficients, source terms, initial and boundary data, and of the associated solution to the differential equation. This then enables the application of elementary analytical tools to explore their stability and accuracy. The assumptions on the smoothness of the data and of the associated analytical solution are however frequently unrealistic. There is a wealth of boundary - and initial - value problems, arising from various applications in physics and engineering, where the data and the corresponding solution exhibit lack of regularity. In such instances classical techniques for the error analysis of finite difference schemes break down. The objective of this book is to develop the mathematical theory of finite difference schemes for linear partial differential equations with nonsmooth solutions. Analysis of Finite Difference Schemes is aimed at researchers and graduate students interested in the mathematical theory of numerical methods for the approximate solution of partial differential equations.
Analysis of Genetic Association Studies (Statistics for Biology and Health)
by Gang Zheng Xiaofeng Zhu Yaning Yang Robert C. ElstonAnalysis of Genetic Association Studies is both a graduate level textbook in statistical genetics and genetic epidemiology, and a reference book for the analysis of genetic association studies. Students, researchers, and professionals will find the topics introduced in Analysis of Genetic Association Studies particularly relevant. The book is applicable to the study of statistics, biostatistics, genetics and genetic epidemiology. In addition to providing derivations, the book uses real examples and simulations to illustrate step-by-step applications. Introductory chapters on probability and genetic epidemiology terminology provide the reader with necessary background knowledge. The organization of this work allows for both casual reference and close study.
Analysis of Heat Equations on Domains
by El Maati OuhabazThis is the first comprehensive reference published on heat equations associated with non self-adjoint uniformly elliptic operators. The author provides introductory materials for those unfamiliar with the underlying mathematics and background needed to understand the properties of heat equations. He then treats Lp properties of solutions to a wide class of heat equations that have been developed over the last fifteen years. These primarily concern the interplay of heat equations in functional analysis, spectral theory and mathematical physics. This book addresses new developments and applications of Gaussian upper bounds to spectral theory. In particular, it shows how such bounds can be used in order to prove Lp estimates for heat, Schrödinger, and wave type equations. A significant part of the results have been proved during the last decade. The book will appeal to researchers in applied mathematics and functional analysis, and to graduate students who require an introductory text to sesquilinear form techniques, semigroups generated by second order elliptic operators in divergence form, heat kernel bounds, and their applications. It will also be of value to mathematical physicists. The author supplies readers with several references for the few standard results that are stated without proofs.
Analysis of Heat Equations on Domains. (LMS-31)
by El-Maati OuhabazThis is the first comprehensive reference published on heat equations associated with non self-adjoint uniformly elliptic operators. The author provides introductory materials for those unfamiliar with the underlying mathematics and background needed to understand the properties of heat equations. He then treats Lp properties of solutions to a wide class of heat equations that have been developed over the last fifteen years. These primarily concern the interplay of heat equations in functional analysis, spectral theory and mathematical physics.This book addresses new developments and applications of Gaussian upper bounds to spectral theory. In particular, it shows how such bounds can be used in order to prove Lp estimates for heat, Schrödinger, and wave type equations. A significant part of the results have been proved during the last decade.The book will appeal to researchers in applied mathematics and functional analysis, and to graduate students who require an introductory text to sesquilinear form techniques, semigroups generated by second order elliptic operators in divergence form, heat kernel bounds, and their applications. It will also be of value to mathematical physicists. The author supplies readers with several references for the few standard results that are stated without proofs.
The Analysis of Household Surveys: A Microeconometric Approach to Development Policy (World Bank Ser.)
by Angus DeatonTwo decades after its original publication, The Analysis of Household Surveys is reissued with a new preface by its author, Sir Angus Deaton, recipient of the 2015 Nobel Prize in Economic Sciences. This classic work remains relevant to anyone with a serious interest in using household survey data to shed light on policy issues. The book reviews the analysis of household survey data, including the construction of household surveys, the econometric tools useful for such analysis, and a range of problems in development policy for which this survey analysis can be applied. Chapter 1 describes the features of survey design that need to be understood in order to undertake appropriate analysis. Chapter 2 discusses the general econometric and statistical issues that arise when using survey data for estimation and inference. Chapter 3 covers the use of survey data to measure welfare, poverty, and distribution. Chapter 4 focuses on the use of household budget data to explore patterns of household demand. Chapter 5 discusses price reform, its effects on equity and efficiency, and how to measure them. Chapter 6 addresses the role of household consumption and saving in economic development. The book includes an appendix providing code and programs using STATA, which can serve as a template for users' own analysis.
Analysis of Images, Social Networks and Texts: 11th International Conference, AIST 2023, Yerevan, Armenia, September 28–30, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14486)
by Dmitry I. Ignatov Michael Khachay Andrey Kutuzov Habet Madoyan Ilya Makarov Irina Nikishina Alexander Panchenko Maxim Panov Panos M. Pardalos Andrey V. Savchenko Evgenii Tsymbalov Elena Tutubalina Sergey ZagoruykoThis book constitutes revised selected papers from the thoroughly refereed proceedings of the 11th International Conference on Analysis of Images, Social Networks and Texts, AIST 2023, held in Yerevan, Armenia, during September 28-30, 2023. The 24 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections as follows: natural language processing; computer vision; data analysis and machine learning; network analysis; and theoretical machine learning and optimization. The book also contains one invited talk in full paper length.
Analysis of Incidence Rates (Chapman & Hall/CRC Biostatistics Series)
by Peter CummingsIncidence rates are counts divided by person-time; mortality rates are a well-known example. Analysis of Incidence Rates offers a detailed discussion of the practical aspects of analyzing incidence rates. Important pitfalls and areas of controversy are discussed. The text is aimed at graduate students, researchers, and analysts in the disciplines of epidemiology, biostatistics, social sciences, economics, and psychology. Features: Compares and contrasts incidence rates with risks, odds, and hazards. Shows stratified methods, including standardization, inverse-variance weighting, and Mantel-Haenszel methods Describes Poisson regression methods for adjusted rate ratios and rate differences. Examines linear regression for rate differences with an emphasis on common problems. Gives methods for correcting confidence intervals. Illustrates problems related to collapsibility. Explores extensions of count models for rates, including negative binomial regression, methods for clustered data, and the analysis of longitudinal data. Also, reviews controversies and limitations. Presents matched cohort methods in detail. Gives marginal methods for converting adjusted rate ratios to rate differences, and vice versa. Demonstrates instrumental variable methods. Compares Poisson regression with the Cox proportional hazards model. Also, introduces Royston-Parmar models. All data and analyses are in online Stata files which readers can download. Peter Cummings is Professor Emeritus, Department of Epidemiology, School of Public Health, University of Washington, Seattle WA. His research was primarily in the field of injuries. He used matched cohort methods to estimate how the use of seat belts and presence of airbags were related to death in a traffic crash. He is author or co-author of over 100 peer-reviewed articles.
Analysis of Industrial Clusters in China
by Zhu YingmingTaking a close look at the national economic system of China, this book defines industrial clusters, then summarizes their measurement indices and identifies their methods. The author identifies 11 industrial clusters and analyses their structural relationships. He studies the relationships between structures and characters of industrial clusters u
Analysis of Infectious Disease Data
by N.G. BeckerThe book gives an up-to-date account of various approaches availablefor the analysis of infectious disease data. Most of the methods havebeen developed only recently, and for those based on particularlymodern mathematics, details of the computation are carefullyillustrated. Interpretation is discussed at some length and the emphasisthroughout is on making statistical inferences about epidemiologicallyimportant parameters.Niels G. Becker is Reader in Statistics at La Trobe University,Australia.
Analysis of Integrated Data (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
by Li-Chun Zhang and Raymond L. ChambersThe advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.
Analysis of Large and Complex Data (Studies in Classification, Data Analysis, and Knowledge Organization #0)
by Adalbert F.X. Wilhelm Hans A. KestlerThis book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis in Marketing; Data Analysis in Finance and Economics; Data Analysis in Medicine and the Life Sciences; Data Analysis in the Social, Behavioural, and Health Care Sciences; Data Analysis in Interdisciplinary Domains; Classification and Subject Indexing in Library and Information Science. The book presents selected papers from the Second European Conference on Data Analysis, held at Jacobs University Bremen in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process.
The Analysis of Linear Economic Systems: Father Maurice Potron’s Pioneering Works (Routledge Studies In The History Of Economics #117)
by Christian Bidard Guido Erreygers Paul A. SamuelsonMaurice Potron (1872-1942), a French Jesuit mathematician, constructed and analyzed a highly original, but virtually unknown economic model. This book presents translated versions of all his economic writings, preceded by a long introduction which sketches his life and environment based on extensive archival research and family documents. Potron had no education in economics and almost no contact with the economists of his time. His primary source of inspiration was the social doctrine of the Church, which had been updated at the end of the nineteenth century. Faced with the ‘economic evils’ of his time, he reacted by utilizing his talents as a mathematician and an engineer to invent and formalize a general disaggregated model in which production, employment, prices and wages are the main unknowns. He introduced four basic principles or normative conditions (‘sufficient production’, the ‘right to rest’, ‘justice in exchange’, and the ‘right to live’) to define satisfactory regimes of production and labour on the one hand, and of prices and wages on the other. He studied the conditions for the existence of these regimes, both on the quantity side and the value side, and he explored the way to implement them. This book makes it clear that Potron was the first author to develop a full input-output model, to use the Perron-Frobenius theorem in economics, to state a duality result, and to formulate the Hawkins-Simon condition. These are all techniques which now belong to the standard toolkit of economists. This book will be of interest to Economics postgraduate students and researchers, and will be essential reading for courses dealing with the history of mathematical economics in general, and linear production theory in particular. Paul A. Samuelson’s short foreword to the book may have been his last academic contribution.
The Analysis of Linear Economic Systems: Father Maurice Potron�s Pioneering Works (Routledge Studies In The History Of Economics #117)
by Christian Bidard Guido Erreygers Paul A. SamuelsonMaurice Potron (1872-1942), a French Jesuit mathematician, constructed and analyzed a highly original, but virtually unknown economic model. This book presents translated versions of all his economic writings, preceded by a long introduction which sketches his life and environment based on extensive archival research and family documents.Potron had no education in economics and almost no contact with the economists of his time. His primary source of inspiration was the social doctrine of the Church, which had been updated at the end of the nineteenth century. Faced with the ‘economic evils’ of his time, he reacted by utilizing his talents as a mathematician and an engineer to invent and formalize a general disaggregated model in which production, employment, prices and wages are the main unknowns. He introduced four basic principles or normative conditions (‘sufficient production’, the ‘right to rest’, ‘justice in exchange’, and the ‘right to live’) to define satisfactory regimes of production and labour on the one hand, and of prices and wages on the other. He studied the conditions for the existence of these regimes, both on the quantity side and the value side, and he explored the way to implement them.This book makes it clear that Potron was the first author to develop a full input-output model, to use the Perron-Frobenius theorem in economics, to state a duality result, and to formulate the Hawkins-Simon condition. These are all techniques which now belong to the standard toolkit of economists. This book will be of interest to Economics postgraduate students and researchers, and will be essential reading for courses dealing with the history of mathematical economics in general, and linear production theory in particular.
Analysis of Longitudinal Data with Example
by You-Gan Wang Liya Fu Sudhir PaulDevelopment in methodology on longitudinal data is fast. Currently, there are a lack of intermediate /advanced level textbooks which introduce students and practicing statisticians to the updated methods on correlated data inference. This book will present a discussion of the modern approaches to inference, including the links between the theories of estimators and various types of efficient statistical models including likelihood-based approaches. The theory will be supported with practical examples of R-codes and R-packages applied to interesting case-studies from a number of different areas. Key Features: •Includes the most up-to-date methods •Use simple examples to demonstrate complex methods •Uses real data from a number of areas •Examples utilize R code
Analysis of Messy Data Volume 1: Designed Experiments, Second Edition
by null George A. Milliken null Dallas E. JohnsonA bestseller for nearly 25 years, Analysis of Messy Data, Volume 1: Designed Experiments helps applied statisticians and researchers analyze the kinds of data sets encountered in the real world. Written by two long-time researchers and professors, this second edition has been fully updated to reflect the many developments that have occurred since t
Analysis of Messy Data, Volume II: Nonreplicated Experiments
by Dallas E. Johnson George A. MillikenResearchers often do not analyze nonreplicated experiments statistically because they are unfamiliar with existing statistical methods that may be applicable. Analysis of Messy Data, Volume II details the statistical methods appropriate for nonreplicated experiments and explores ways to use statistical software to make the required computations feasible.
Analysis of Messy Data, Volume III: Analysis of Covariance
by null George A. Milliken null Dallas E. JohnsonAnalysis of covariance is a very useful but often misunderstood methodology for analyzing data where important characteristics of the experimental units are measured but not included as factors in the design. Analysis of Messy Data, Volume 3: Analysis of Covariance takes the unique approach of treating the analysis of covariance problem by looking