Modern Methods for Robust Regression offers a brief but in-depth treatment of various methods for detecting and properly handling influential cases in regression analysis. This volume, geared toward both future and practicing social scientists, is unique in that it takes an applied approach and offers readers empirical examples to illustrate key concepts. It is ideal for readers who are interested in the issues related to outliers and influential cases.
Key Features. Defines key terms necessary to understanding the robustness of an estimator: Because they form the basis of robust regression techniques, the book also deals with various measures of location and scale. Addresses the robustness of validity and efficiency: After having described the robustness of validity for an estimator, the author discusses its efficiency. Focuses on the impact of outliers: The book compares the robustness of a wide variety of estimators that attempt to limit the influence of unusual observations. Gives an overview of some traditional techniques: Both formal statistical tests and graphical methods detect influential cases in the general linear model. Offers a Web appendix: This volume provides readers with the data and the R code for the examples used in the book.
Modern Robust Statistical Methods: Basics with Illustrations Using Psychobiological Data. Modern Regression Methods. Workshop Modern methods for robust regression.
Intended Audience This is an excellent text for intermediate and advanced Quantitative Methods and Statistics courses offered at the graduate level across the social sciences. Learn more about 'The Little Green Book' - QASS Series!
Author by: Robert Andersen Language: en Publisher by: SAGE Format Available: PDF, ePub, Mobi Total Read: 73 Total Download: 887 File Size: 55,9 Mb Description: Geared towards both future and practising social scientists, this book takes an applied approach and offers readers empirical examples to illustrate key concepts. It includes: applied coverage of a topic that has traditionally been discussed from a theoretical standpoint; empirical examples to illustrate key concepts; a web appendix that provides readers with the data and the R-code for the examples used in the book. Author by: Peter J. Rousseeuw Language: en Publisher by: John Wiley & Sons Format Available: PDF, ePub, Mobi Total Read: 80 Total Download: 738 File Size: 45,8 Mb Description: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. 'The writing style is clear and informal, and much of the discussion is oriented to application.
In short, the book is a keeper.' –Mathematical Geology 'I would highly recommend the addition of this book to the libraries of both students and professionals. It is a useful textbook for the graduate student, because it emphasizes both the philosophy and practice of robustness in regression settings, and it provides excellent examples of precise, logical proofs of theorems.Even for those who are familiar with robustness, the book will be a good reference because it consolidates the research in high-breakdown affine equivariant estimators and includes an extensive bibliography in robust regression, outlier diagnostics, and related methods. The aim of this book, the authors tell us, is ‘to make robust regression available for everyday statistical practice.’ Rousseeuw and Leroy have included all of the necessary ingredients to make this happen.' –Journal of the American Statistical Association.
Author by: Valentim R. Alferes Language: en Publisher by: SAGE Format Available: PDF, ePub, Mobi Total Read: 89 Total Download: 734 File Size: 47,9 Mb Description: This book provides a conceptual systematization and a practical tool for the randomization of between-subjects and within-subjects experimental designs in social, behavioural, and health sciences. The author adopts a pedagogical strategy that allows the reader to implement all randomization methods by relying on the materials given in the appendices and using the common features included in any word processor software. In the companion website (www.fpce.uc.pt/niips/randmethods), along with other supplementary materials, the reader can freely download IBM SPSS and R versions of SCRAED, a package that performs simple and complex random assignment in experimental design, including the 18 randomization methods presented in Chapters 2 and 3.
Author by: Iain Pardoe Language: en Publisher by: John Wiley & Sons Format Available: PDF, ePub, Mobi Total Read: 91 Total Download: 448 File Size: 41,5 Mb Description: Praise for the First Edition 'The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions. The examples are wonderful.'
—The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level.
The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work. Author by: James Alan Fox Language: en Publisher by: SAGE Publications Format Available: PDF, ePub, Mobi Total Read: 10 Total Download: 578 File Size: 46,7 Mb Description: Randomized response is a data collection strategy specifically designed for surveys of a sensitive nature. By establishing a probabilistic connection between question and answer, randomized response and related methods protect respondents who are asked to disclose personal information. Covering a half century of theoretical and applied research, the Second Edition of James Alan Fox’s Randomized Response and Related Methods significantly updates and expands what was, at the time, the first comprehensive and practical guide to randomized response. Author by: Risk Management Institute Language: en Publisher by: World Scientific Format Available: PDF, ePub, Mobi Total Read: 83 Total Download: 990 File Size: 43,6 Mb Description: Global Credit Review is an annual publication that provides an overview of the most important developments in global credit markets and the regulatory landscape. The third volume provides some critical analysis, reviews the introduction of new regulations and also offers new insights to address the challenges ahead. The carefully selected chapters touch on current topics such as: the measurement of systemic risk, reserve requirements and its role in monetary policy, the application of the Basel II default definition by credit risk assessment systems, and changes in credit portfolio management, amongst others.
Recent evolutions of the Risk Management Institute's Credit Research Initiative are also reported, including a comprehensive overview of the technical details on the implementation of the current RMI-CRI corporate default prediction model. With its distinctive focus on topics related to credit markets and credit risk, this is an invaluable publication for finance professionals, policy makers and academics with an interest in credit markets. Contents:Systemic Risk in Europe (Eric Jondeau and Michael Rockinger)Changes in the Ratings Game — An Update on Various Developments (RMI staff)Reserve Requirements as Window Guidance in China (Violaine Cousin)The Implementation of the Basel II Default Definition by Credit Risk Assessment Systems: An Analysis of Possible Aggregation Procedures (Markus Bingmer and Laura Auria)Can Credit-Scoring Models Effectively Predict Microloans Default? Statistical Evidence from the Tunisian Microfinance Bank (Ibtissem Baklouti and Abdelfettah Bouri)Stepping Up to the Liquidity Challenge: The Changing Role of Credit Portfolio Management (IACPM and KPMG)NUS-RMI Credit Research Initiative Technical Report (Version: 2013, Update 2b) (RMI staff) Readership: Finance professionals, policy makers and academics with an interest in credit markets. Mathematics book pdf. Author by: Robert L.
Kaufman Language: en Publisher by: SAGE Publications Format Available: PDF, ePub, Mobi Total Read: 17 Total Download: 694 File Size: 44,6 Mb Description: Heteroskedasticity in Regression: Detection and Correction, by Robert Kaufman, covers the commonly ignored topic of heteroskedasticity (unequal error variances) in regression analyses and provides a practical guide for how to proceed in terms of testing and correction. Emphasizing how to apply diagnostic tests and corrections for heteroskedasticity in actual data analyses, the monograph offers three approaches for dealing with heteroskedasticity: (1) variance-stabilizing transformations of the dependent variable; (2) calculating robust standard errors, or heteroskedasticity-consistent standard errors; and (3) generalized least squares estimation coefficients and standard errors. The detection and correction of heteroskedasticity is illustrated with three examples that vary in terms of sample size and the types of units analyzed (individuals, households, U.S. Intended as a supplementary text for graduate-level courses and a primer for quantitative researchers, the book fills the gap between the limited coverage of heteroskedasticity provided in applied regression textbooks and the more theoretical statistical treatment in advanced econometrics textbooks. Author by: Larry D.
Schroeder Language: en Publisher by: SAGE Publications Format Available: PDF, ePub, Mobi Total Read: 95 Total Download: 447 File Size: 44,6 Mb Description: Understanding Regression Analysis: An Introductory Guide by Larry D. Schroeder, David L.
Robert Anderson
Sjoquist, and Paula E. Stephan presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style. It illustrates how regression coefficients are estimated, interpreted, and used in a variety of settings within the social sciences, business, law, and public policy. Packed with applied examples and using few equations, the book walks readers through elementary material using a verbal, intuitive interpretation of regression coefficients, associated statistics, and hypothesis tests. The Second Edition features updated examples and new references to modern software output. Author by: Colin Lewis-Beck Language: en Publisher by: SAGE Publications Format Available: PDF, ePub, Mobi Total Read: 67 Total Download: 316 File Size: 55,5 Mb Description: Known for its readability and clarity, this Second Edition of the best-selling Applied Regression provides an accessible introduction to regression analysis for social scientists and other professionals who want to model quantitative data.
After covering the basic idea of fitting a straight line to a scatter of data points, the text uses clear language to explain both the mathematics and assumptions behind the simple linear regression model. Authors Colin Lewis-Beck and Michael Lewis-Beck then cover more specialized subjects of regression analysis, such as multiple regression, measures of model fit, analysis of residuals, interaction effects, multicollinearity, and prediction. Throughout the text, graphical and applied examples help explain and demonstrate the power and broad applicability of regression analysis for answering scientific questions. Author by: Isabella Morlini Language: en Publisher by: Springer Format Available: PDF, ePub, Mobi Total Read: 40 Total Download: 469 File Size: 53,5 Mb Description: This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment.
The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.