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Author: John Fox
Publisher: SAGE
Published: 1991-08-14
Total Pages: 100
ISBN-13: 9780803939714
DOWNLOAD EBOOKExplaining the techniques needed for exploring problems that comprise a regression analysis, and for determining whether certain assumptions appear reasonable, this book covers such topics as the problem of collinearity in multiple regression, non-normality of errors, and discrete data.
Author: David A. Belsley
Publisher: Wiley-Interscience
Published: 1980-07-08
Total Pages: 326
ISBN-13:
DOWNLOAD EBOOKDetecting influential observations and outliers - Detecting and assessing collinearity - Applications and remedies - Research issues and directions for extensions.
Author: John Fox
Publisher: SAGE Publications
Published: 2019-12-09
Total Pages: 138
ISBN-13: 1544375212
DOWNLOAD EBOOKRegression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (straight-line) relationship between the response and an explanatory variable, is the assumption of linearity warranted? Regression diagnostics not only reveal deficiencies in a regression model that has been fit to data but in many instances may suggest how the model can be improved. The Second Edition of this bestselling volume by John Fox considers two important classes of regression models: the normal linear regression model (LM), in which the response variable is quantitative and assumed to have a normal distribution conditional on the values of the explanatory variables; and generalized linear models (GLMs) in which the conditional distribution of the response variable is a member of an exponential family. R code and data sets for examples within the text can be found on an accompanying website.
Author: John Fox
Publisher: SAGE
Published: 2000-01-20
Total Pages: 100
ISBN-13: 9780761915850
DOWNLOAD EBOOKNonparametric simple regression forms the basis for nonparametric multiple regression and directly supplies the building blocks for the type of nonparametric multiple regression called additive regression.
Author: Anthony Atkinson
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 342
ISBN-13: 1461211603
DOWNLOAD EBOOKGraphs are used to understand the relationship between a regression model and the data to which it is fitted. The authors develop new, highly informative graphs for the analysis of regression data and for the detection of model inadequacies. As well as illustrating new procedures, the authors develop the theory of the models used, particularly for generalized linear models. The book provides statisticians and scientists with a new set of tools for data analysis. Software to produce the plots is available on the authors website.
Author: David A. Belsley
Publisher: John Wiley & Sons
Published: 2005-02-25
Total Pages: 292
ISBN-13: 0471725145
DOWNLOAD EBOOKThe Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "The title of the book more or less sums up the contents. Itappears to me to represent a real breakthrough in the art ofdealing in ‘unconventional’ data. . . . I found thewhole book both readable and enjoyable. It is suitable for dataanalysts, academic statisticians, and professional softwarewriters." –Journal of the Royal Statistical Society "The book assumes a working knowledge of all of the principalresults and techniques used in least squares multiple regression,as expressed in vector and matrix notation. Given this background,the book is clear and easy to use. . . . The techniques areillustrated in great detail with practical data sets fromeconometrics." –Short Book Reviews, International Statistical Institute Regression Diagnostics: Identifying Influential Data and Sourcesof Collinearity provides practicing statisticians andeconometricians with new tools for assessing quality andreliability of regression estimates. Diagnostic techniques aredeveloped that aid in the systematic location of data points thatare unusual or inordinately influential; measure the presence andintensity of collinear relations among the regression data; andhelp to identify variables involved in each and pinpoint estimatedcoefficients potentially most adversely affected. The bookemphasizes diagnostics and includes suggestions for remedialaction
Author: Sanford Weisberg
Publisher: John Wiley & Sons
Published: 2013-06-07
Total Pages: 266
ISBN-13: 1118625951
DOWNLOAD EBOOKMaster linear regression techniques with a new edition of a classic text Reviews of the Second Edition: "I found it enjoyable reading and so full of interesting material that even the well-informed reader will probably find something new . . . a necessity for all of those who do linear regression." —Technometrics, February 1987 "Overall, I feel that the book is a valuable addition to the now considerable list of texts on applied linear regression. It should be a strong contender as the leading text for a first serious course in regression analysis." —American Scientist, May–June 1987 Applied Linear Regression, Third Edition has been thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, the Third Edition stresses the use of graphical methods in an effort to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results. The Third Edition incorporates new material reflecting the latest advances, including: Use of smoothers to summarize a scatterplot Box-Cox and graphical methods for selecting transformations Use of the delta method for inference about complex combinations of parameters Computationally intensive methods and simulation, including the bootstrap method Expanded chapters on nonlinear and logistic regression Completely revised chapters on multiple regression, diagnostics, and generalizations of regression Readers will also find helpful pedagogical tools and learning aids, including: More than 100 exercises, most based on interesting real-world data Web primers demonstrating how to use standard statistical packages, including R, S-Plus®, SPSS®, SAS®, and JMP®, to work all the examples and exercises in the text A free online library for R and S-Plus that makes the methods discussed in the book easy to use With its focus on graphical methods and analysis, coupled with many practical examples and exercises, this is an excellent textbook for upper-level undergraduates and graduate students, who will quickly learn how to use linear regression analysis techniques to solve and gain insight into real-life problems.
Author: Richard B. Darlington
Publisher: Guilford Publications
Published: 2016-08-22
Total Pages: 689
ISBN-13: 1462527981
DOWNLOAD EBOOKEmphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book's examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable’s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.
Author: Samprit Chatterjee
Publisher: John Wiley & Sons
Published: 2006-10-20
Total Pages: 403
ISBN-13: 0470055456
DOWNLOAD EBOOKThe essentials of regression analysis through practical applications Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgement. Regression Analysis by Example, Fourth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression diagnostics, transformation, multicollinearity, logistic regression, and robust regression. This new edition features the following enhancements: Chapter 12, Logistic Regression, is expanded to reflect the increased use of the logit models in statistical analysis A new chapter entitled Further Topics discusses advanced areas of regression analysis Reorganized, expanded, and upgraded exercises appear at the end of each chapter A fully integrated Web page provides data sets Numerous graphical displays highlight the significance of visual appeal Regression Analysis by Example, Fourth Edition is suitable for anyone with an understanding of elementary statistics. Methods of regression analysis are clearly demonstrated, and examples containing the types of irregularities commonly encountered in the real world are provided. Each example isolates one or two techniques and features detailed discussions of the techniques themselves, the required assumptions, and the evaluated success of each technique. The methods described throughout the book can be carried out with most of the currently available statistical software packages, such as the software package R. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Author: Scott Menard
Publisher: SAGE
Published: 2002
Total Pages: 130
ISBN-13: 9780761922087
DOWNLOAD EBOOKThe focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.
