Search Results: statistical-methodological-aspects-statistics-in-practice

Statistical and Methodological Aspects of Oral Health Research

Author: Emmanuel Lesaffre

Publisher: John Wiley & Sons

ISBN: 9780470744123

Category: Mathematics

Page: 408

View: 5937

Statistical and Methodological Aspects of Oral Health Research provides oral health researchers with an overview of the methodological aspects that are important in planning, conducting and analyzing their research projects whilst also providing biostatisticians with an idea of the statistical problems that arise when tackling oral health research questions. This collection presents critical reflections on oral health research and offers advice on practical aspects of setting up research whilst introducing the reader to basic as well as advanced statistical methodology. Features: An introduction to research methodology and an exposition of the state of the art. A variety of examples from oral health research. Contributions from well-known oral health researchers, epidemiologists and biostatisticians, all of whom have rich experience in this area. Recent developments in statistical methodology prompted by a variety of dental applications. Presenting both an introduction to research methodology and an exposition of the latest advances in oral health research, this book will appeal both beginning and experienced oral health researchers as well as biostatisticians and epidemiologists.

Statistical and Methodological Aspects of Oral Health Research

Author: Emmanuel Lesaffre

Publisher: John Wiley & Sons

ISBN: 9780470744123

Category: Mathematics

Page: 408

View: 1281

Statistical and Methodological Aspects of Oral Health Research provides oral health researchers with an overview of the methodological aspects that are important in planning, conducting and analyzing their research projects whilst also providing biostatisticians with an idea of the statistical problems that arise when tackling oral health research questions. This collection presents critical reflections on oral health research and offers advice on practical aspects of setting up research whilst introducing the reader to basic as well as advanced statistical methodology. Features: An introduction to research methodology and an exposition of the state of the art. A variety of examples from oral health research. Contributions from well-known oral health researchers, epidemiologists and biostatisticians, all of whom have rich experience in this area. Recent developments in statistical methodology prompted by a variety of dental applications. Presenting both an introduction to research methodology and an exposition of the latest advances in oral health research, this book will appeal both beginning and experienced oral health researchers as well as biostatisticians and epidemiologists.

The Gini Methodology

A Primer on a Statistical Methodology

Author: Shlomo Yitzhaki,Edna Schechtman

Publisher: Springer Science & Business Media

ISBN: 1461447208

Category: Mathematics

Page: 548

View: 5206

Gini's mean difference (GMD) was first introduced by Corrado Gini in 1912 as an alternative measure of variability. GMD and the parameters which are derived from it (such as the Gini coefficient or the concentration ratio) have been in use in the area of income distribution for almost a century. In practice, the use of GMD as a measure of variability is justified whenever the investigator is not ready to impose, without questioning, the convenient world of normality. This makes the GMD of critical importance in the complex research of statisticians, economists, econometricians, and policy makers. This book focuses on imitating analyses that are based on variance by replacing variance with the GMD and its variants. In this way, the text showcases how almost everything that can be done with the variance as a measure of variability, can be replicated by using Gini. Beyond this, there are marked benefits to utilizing Gini as opposed to other methods. One of the advantages of using Gini methodology is that it provides a unified system that enables the user to learn about various aspects of the underlying distribution. It also provides a systematic method and a unified terminology. Using Gini methodology can reduce the risk of imposing assumptions that are not supported by the data on the model. With these benefits in mind the text uses the covariance-based approach, though applications to other approaches are mentioned as well.

Applied Mixed Models in Medicine

Author: Helen Brown,Robin Prescott

Publisher: John Wiley & Sons

ISBN: 1118778243

Category: Medical

Page: 536

View: 9966

A fully updated edition of this key text on mixed models, focusing on applications in medical research The application of mixed models is an increasingly popular way of analysing medical data, particularly in the pharmaceutical industry. A mixed model allows the incorporation of both fixed and random variables within a statistical analysis, enabling efficient inferences and more information to be gained from the data. There have been many recent advances in mixed modelling, particularly regarding the software and applications. This third edition of Brown and Prescott’s groundbreaking text provides an update on the latest developments, and includes guidance on the use of current SAS techniques across a wide range of applications. Presents an overview of the theory and applications of mixed models in medical research, including the latest developments and new sections on incomplete block designs and the analysis of bilateral data. Easily accessible to practitioners in any area where mixed models are used, including medical statisticians and economists. Includes numerous examples using real data from medical and health research, and epidemiology, illustrated with SAS code and output. Features the new version of SAS, including new graphics for model diagnostics and the procedure PROC MCMC. Supported by a website featuring computer code, data sets, and further material. This third edition will appeal to applied statisticians working in medical research and the pharmaceutical industry, as well as teachers and students of statistics courses in mixed models. The book will also be of great value to a broad range of scientists, particularly those working in the medical and pharmaceutical areas.

Main Economic Indicators Comparative Methodological Analysis: Wage related statistics Volume 2002 Supplement 3

Comparative Methodological Analysis: Wage related statistics Volume 2002 Supplement 3

Author: OECD

Publisher: OECD Publishing

ISBN: 9264175784

Category:

Page: 152

View: 3554

This publication compares key aspects of statistical methodologies used by OECD member countries in the compilation of wage related statistics. Such statistics comprise wages and earnings, minimum wages, labour costs and prices, unit labour costs and household income.

Advances on Theoretical and Methodological Aspects of Probability and Statistics

Author: N. Balakrishnan

Publisher: CRC Press

ISBN: 9780203493205

Category: Mathematics

Page: 560

View: 1696

At the International Indian Statistical Association Conference, held at McMaster University in Ontario, Canada, participants focused on advancements in theory and methodology of probability and statistics. This is one of two volumes containing invited papers from the meeting. The 32 chapters deal with different topics of interest, including stochastic processes and inference, distributions and characterizations, inference, Bayesian inference, selection methods, regression methods, and methods in health research. The text is ideal for applied mathematicians, statisticians, and researchers in the field.

Data Analysis in Community and Landscape Ecology

Author: C. J. F. Ter Braak,O. F. R. van Tongeren

Publisher: Cambridge University Press

ISBN: 9780521475747

Category: Mathematics

Page: 299

View: 9155

Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.

Doing Statistical Mediation and Moderation

Author: Paul E. Jose

Publisher: Guilford Press

ISBN: 1462508219

Category: Psychology

Page: 336

View: 8212

"Written in a friendly, conversational style, this book offers a hands-on approach to statistical mediation and moderation for both beginning researchers and those familiar with modeling. Starting with a gentle review of regression-based analysis, Paul Jose covers basic mediation and moderation techniques before moving on to advanced topics in multilevel modeling, structural equation modeling, and hybrid combinations, such as moderated mediation. User-friendly features include numerous graphs and carefully worked-through examples; "Helpful Suggestions" about procedures and pitfalls; "Knowledge Boxes" delving into special topics, such as dummy coding; and end-of-chapter exercises and problems (with answers). The companion website provides downloadable sample data sets that are used in the book to demonstrate particular analytic strategies, and explains how researchers and students can execute analyses using Jose's online programs, MedGraph and ModGraph. Appendices present SPSS, AMOS, and Mplus syntax for conducting the key types of analyses"--

Handbook of Ethics in Quantitative Methodology

Author: Sonya K. Sterba

Publisher: Taylor & Francis

ISBN: 113688873X

Category: BUSINESS & ECONOMICS

Page: 544

View: 7364

"Part 1 presents ethical frameworks that cross-cut design, analysis, and modeling in the behavioral sciences. Part 2 focuses on ideas for disseminating ethical training in statistics courses. Part 3 considers the ethical aspects of selecting measurement instruments and sample size planning and explores issues related to high stakes testing, the defensibility of experimental vs. quasi-experimental research designs, and ethics in program evaluation. Decision points that shape a researchers' approach to data analysis are examined in Part 4 - when and why analysts need to account for how the sample was selected, how to evaluate tradeoffs of hypothesis-testing vs. estimation, and how to handle missing data. Ethical issues that arise when using techniques such as factor analysis or multilevel modeling and when making causal inferences are also explored. The book concludes with ethical aspects of reporting meta-analyses, of cross-disciplinary statistical reform, and of the publication process.

Methodology in Robust and Nonparametric Statistics

Author: Jana Jurečková,Pranab Kumar Sen,Jan Picek

Publisher: CRC Press

ISBN: 1439840695

Category: Mathematics

Page: 410

View: 7251

Robust and nonparametric statistical methods have their foundation in fields ranging from agricultural science to astronomy, from biomedical sciences to the public health disciplines, and, more recently, in genomics, bioinformatics, and financial statistics. These disciplines are presently nourished by data mining and high-level computer-based algorithms, but to work actively with robust and nonparametric procedures, practitioners need to understand their background. Explaining the underpinnings of robust methods and recent theoretical developments, Methodology in Robust and Nonparametric Statistics provides a profound mathematically rigorous explanation of the methodology of robust and nonparametric statistical procedures. Thoroughly up-to-date, this book Presents multivariate robust and nonparametric estimation with special emphasis on affine-equivariant procedures, followed by hypotheses testing and confidence sets Keeps mathematical abstractions at bay while remaining largely theoretical Provides a pool of basic mathematical tools used throughout the book in derivations of main results The methodology presented, with due emphasis on asymptotics and interrelations, will pave the way for further developments on robust statistical procedures in more complex models. Using examples to illustrate the methods, the text highlights applications in the fields of biomedical science, bioinformatics, finance, and engineering. In addition, the authors provide exercises in the text.

SAS for Data Analysis

Intermediate Statistical Methods

Author: Mervyn G. Marasinghe,William J. Kennedy

Publisher: Springer Science & Business Media

ISBN: 9780387773728

Category: Mathematics

Page: 558

View: 1604

This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.

Statistical Aspects of the Microbiological Examination of Foods

Author: Basil Jarvis

Publisher: Academic Press

ISBN: 0128039744

Category: Technology & Engineering

Page: 352

View: 1516

Statistical Aspects of the Microbiological Examination of Foods, Third Edition, updates some important statistical procedures following intensive collaborative work by many experts in microbiology and statistics, and corrects typographic and other errors present in the previous edition. Following a brief introduction to the subject, basic statistical concepts and procedures are described including both theoretical and actual frequency distributions that are associated with the occurrence of microorganisms in foods. This leads into a discussion of the methods for examination of foods and the sources of statistical and practical errors associated with the methods. Such errors are important in understanding the principles of measurement uncertainty as applied to microbiological data and the approaches to determination of uncertainty. The ways in which the concept of statistical process control developed many years ago to improve commercial manufacturing processes can be applied to microbiological examination in the laboratory. This is important in ensuring that laboratory results reflect, as precisely as possible, the microbiological status of manufactured products through the concept and practice of laboratory accreditation and proficiency testing. The use of properly validated standard methods of testing and the verification of ‘in house’ methods against internationally validated methods is of increasing importance in ensuring that laboratory results are meaningful in relation to development of and compliance with established microbiological criteria for foods. The final chapter of the book reviews the uses of such criteria in relation to the development of and compliance with food safety objectives. Throughout the book the theoretical concepts are illustrated in worked examples using real data obtained in the examination of foods and in research studies concerned with food safety. Includes additional figures and tables together with many worked examples to illustrate the use of specific procedures in the analysis of data obtained in the microbiological examination of foods Offers completely updated chapters and six new chapters Brings the reader up to date and allows easy access to individual topics in one place Corrects typographic and other errors present in the previous edition

Journal of the Royal Statistical Society. Series A, Statistics in society

Author: N.A

Publisher: N.A

ISBN: N.A

Category:

Page: N.A

View: 4967

Statistical Methods for Trend Detection and Analysis in the Environmental Sciences

Author: Richard Chandler,Marian Scott

Publisher: John Wiley & Sons

ISBN: 111999196X

Category: Mathematics

Page: 388

View: 8503

The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.

Statistical Concepts and Applications in Clinical Medicine

Author: John Aitchison,Jim W. Kay,Ian J. Lauder

Publisher: CRC Press

ISBN: 0203497414

Category: Mathematics

Page: 360

View: 8579

Statistical Concepts and Applications in Clinical Medicine presents a unique, problem-oriented approach to using statistical methods in clinical medical practice through each stage of the clinical process, including observation, diagnosis, and treatment. The authors present each consultative problem in its original form, then describe the process of problem formulation, develop the appropriate statistical models, and interpret the statistical analysis in the context of the real problem. Their treatment provides clear, accessible explanations of statistical methods. The text includes end-of-chapter exercises that help develop formulatory, analytic, and interpretative skills.

Main Economic Indicators Comparative Methodological Analysis: Industry, Retail and Construction Indicators Volume 2002 Supplement 1

Comparative Methodological Analysis: Industry, Retail and Construction Indicators Volume 2002 Supplement 1

Author: OECD

Publisher: OECD Publishing

ISBN: 9264196463

Category:

Page: 80

View: 9177

This publication compares key aspects of statistical methodologies used by OECD Member countries in the compilation of industry, retail and construction indicators.

Main Economic Indicators Comparative Methodological Analysis: Consumer and Producer Price Indices Volume 2002 Supplement 2

Comparative Methodological Analysis: Consumer and Producer Price Indices Volume 2002 Supplement 2

Author: OECD

Publisher: OECD Publishing

ISBN: 9264175776

Category:

Page: 88

View: 6263

This publication compares key aspects of statistical methodologies used by OECD member countries in the compilation of price indicators.

Research Methods and Statistics in Psychology

Author: S Alexander Haslam,Craig McGarty

Publisher: SAGE

ISBN: 1446204707

Category: Psychology

Page: 520

View: 6026

'The strength of this book is in the determined approach it takes to helping the reader learn the subject matter by the inclusion of explanations of key terms and exercises. If coupled with tutorial support, this will encourage students to work harder at the subject matter - always a challenge in what many students perceive as the least accessible and interesting part of psychology. It is well worth considering as a core methods text for undergraduates or for masters students new to psychology'- John Hegarty, Times Higher Educational Supplement, Textbook Guide Research Methods and Statistics in Psychology is an accessible introduction to the principal research methods and statistical procedures that underpin psychological research. With a broad range of support materials and features it is the ideal textbook to accompany both a first and second year course. Key features of this new textbook: - Accompanying website: an interactive resource for both both teachers and students including powerpoint slides of lecture notes, self-test multiple choice questions and answers for students as well as other on-line features. To access these please click on the Companion Website logo above - Coverage of the full research process in psychology from the ground up, addressing issues to do with research goals, problem definition and hypothesis, methodological choices and strategy and ethical controversies. - Complete coverage of the key quantitative and qualitative methods now recognised in psychology. - A host of textbook features including checklists of research evaluation and improvement, discussion questions and exercises; and annotated further reading at the end of every chapter. - Appendices in the back of the textbook in conjunction with the accompanying website - step-by-step guide to performing key statistical tests and a guide to writing up experiments and reports in psychology. Research Methods and Statistics in Psychology is a comprehensive and student-friendly introductory textbook that deals with psychological research issues in depth, but which places an emphasis on the conceptual and practical skills necessary to become a good researcher.

An Introduction to Statistical Learning

with Applications in R

Author: Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani

Publisher: Springer Science & Business Media

ISBN: 1461471389

Category: Mathematics

Page: 426

View: 3422

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Computer Age Statistical Inference

Algorithms, Evidence, and Data Science

Author: Bradley Efron,Trevor Hastie

Publisher: Cambridge University Press

ISBN: 1108107958

Category: Mathematics

Page: N.A

View: 8395

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

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