Download or read book Coping with Multicollinearity written by B. Desta Fekedulegn and published by . This book was released on 2002 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multiple Regression and Beyond written by Timothy Z. Keith and published by Routledge. This book was released on 2019-01-14 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Companion Website materials: https://tzkeith.com/ Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. This book: • Covers both MR and SEM, while explaining their relevance to one another • Includes path analysis, confirmatory factor analysis, and latent growth modeling • Makes extensive use of real-world research examples in the chapters and in the end-of-chapter exercises • Extensive use of figures and tables providing examples and illustrating key concepts and techniques New to this edition: • New chapter on mediation, moderation, and common cause • New chapter on the analysis of interactions with latent variables and multilevel SEM • Expanded coverage of advanced SEM techniques in chapters 18 through 22 • International case studies and examples • Updated instructor and student online resources
Download or read book Multiple Regression in Practice written by William Dale Berry and published by SAGE. This book was released on 1985-05 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors provide a systematic treatment of the major problems involved in using regression analysis. They clearly and concisely discuss the consequences of violating the assumptions of the regression model, procedures for detecting violations, and strategies for dealing with these problems.
Download or read book Serious Stat written by Thomas Baguley and published by Bloomsbury Publishing. This book was released on 2018-01-24 with total page 864 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ideal for experienced students and researchers in the social sciences who wish to refresh or extend their understanding of statistics, and to apply advanced statistical procedures using SPSS or R. Key theory is reviewed and illustrated with examples of how to apply these concepts using real data.
Download or read book Statistical Rethinking written by Richard McElreath and published by CRC Press. This book was released on 2018-01-03 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.
Download or read book Mixed Effects Models and Extensions in Ecology with R written by Alain Zuur and published by Springer Science & Business Media. This book was released on 2009-03-05 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive modelling, GAM and GLM, and then discusses dealing with spatial or temporal dependencies and nested data.
Download or read book Linear Regression Analysis written by Xin Yan and published by World Scientific. This book was released on 2009 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the techniques described in the book. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject area." --Book Jacket.
Download or read book Research Paper NE written by and published by . This book was released on 1987 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stress Coping and Development written by Carolyn M. Aldwin and published by Guilford Press. This book was released on 2009-10-14 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: How do people cope with stressful experiences? What makes a coping strategy effective for a particular individual? This volume comprehensively examines the nature of psychosocial stress and the implications of different coping strategies for adaptation and health across the lifespan. Carolyn M. Aldwin synthesizes a vast body of knowledge within a conceptual framework that emphasizes the transactions between mind and body and between persons and environments. She analyzes different kinds of stressors and their psychological and physiological effects, both negative and positive. Ways in which coping is influenced by personality, relationships, situational factors, and culture are explored. The book also provides a methodological primer for stress and coping research, critically reviewing available measures and data analysis techniques.
Download or read book Learning Statistics Using R written by Randall E. Schumacker and published by SAGE Publications. This book was released on 2014-01-28 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing easy-to-use R script programs that teach descriptive statistics, graphing, and other statistical methods, Learning Statistics Using R shows readers how to run and utilize R, a free integrated statistical suite that has an extensive library of functions. Randall E. Schumacker’s comprehensive book describes in detail the processing of variables in statistical procedures. Covering a wide range of topics, from probability and sampling distribution to statistical theorems and chi-square, this introductory book helps readers learn not only how to use formulae to calculate statistics, but also how specific statistics fit into the overall research process. Learning Statistics Using R covers data input from vectors, arrays, matrices and data frames, as well as the input of data sets from SPSS, SAS, STATA and other software packages. Schumacker’s text provides the freedom to effectively calculate, manipulate, and graphically display data, using R, on different computer operating systems without the expense of commercial software. Learning Statistics Using R places statistics within the framework of conducting research, where statistical research hypotheses can be directly addressed. Each chapter includes discussion and explanations, tables and graphs, and R functions and outputs to enrich readers′ understanding of statistics through statistical computing and modeling.
Download or read book Regression Analysis by Example written by Samprit Chatterjee and published by John Wiley & Sons. This book was released on 2006-10-20 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 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.
Download or read book Statistical Analysis and Data Display written by Richard M. Heiberger and published by Springer Science & Business Media. This book was released on 2004-07-28 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings—for all the methods they cover. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. This book can serve as a standalone text for statistics majors at the master's level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays. The authors provide and discuss S-Plus, R, and SAS executable functions and macros for all new graphical display formats. All graphs and tabular output in the book were constructed using these programs. Complete transcripts for all examples and figures are provided for readers to use as models for their own analyses. Richard M. Heiberger and Burt Holland are both Professors in the Department of Statistics at Temple University and elected Fellows of the American Statistical Association. Richard M. Heiberger participated in the design of the S-Plus linear model and analysis of variance commands while on research leave at Bell Labs in 1987–88 and has been closely involved as a beta tester and user of S-Plus. Burt Holland has made many research contributions to linear modeling and simultaneous statistical inference, and frequently serves as a consultant to medical investigators. Both teach the Temple University course sequence that inspired them to write this text.
Download or read book Theory Based Data Analysis for the Social Sciences written by Carol S. Aneshensel and published by SAGE. This book was released on 2013 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
Download or read book Econometrics in Theory and Practice written by Panchanan Das and published by Springer Nature. This book was released on 2019-09-05 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software. It serves as a basic text for those who wish to learn and apply econometric analysis in empirical research. The level of presentation is as simple as possible to make it useful for undergraduates as well as graduate students. It contains several examples with real data and Stata programmes and interpretation of the results. While discussing the statistical tools needed to understand empirical economic research, the book attempts to provide a balance between theory and applied research. Various concepts and techniques of econometric analysis are supported by carefully developed examples with the use of statistical software package, Stata 15.1, and assumes that the reader is somewhat familiar with the Strata software. The topics covered in this book are divided into four parts. Part I discusses introductory econometric methods for data analysis that economists and other social scientists use to estimate the economic and social relationships, and to test hypotheses about them, using real-world data. There are five chapters in this part covering the data management issues, details of linear regression models, the related problems due to violation of the classical assumptions. Part II discusses some advanced topics used frequently in empirical research with cross section data. In its three chapters, this part includes some specific problems of regression analysis. Part III deals with time series econometric analysis. It covers intensively both the univariate and multivariate time series econometric models and their applications with software programming in six chapters. Part IV takes care of panel data analysis in four chapters. Different aspects of fixed effects and random effects are discussed here. Panel data analysis has been extended by taking dynamic panel data models which are most suitable for macroeconomic research. The book is invaluable for students and researchers of social sciences, business, management, operations research, engineering, and applied mathematics.
Download or read book Role of Attribution Style and Coping Strategy Selection in the Relationship Between Peer Victimization and Outcomes Among Economically Disadvantaged Students written by Juliana Levon Raskauskas and published by . This book was released on 2005 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Multivariate Social Scientist written by Graeme D Hutcheson and published by SAGE. This book was released on 1999-05-19 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Starting from simple hypothesis testing and then moving towards model-building, this valuable book takes readers through the basics of multivariate analysis including: which tests to use on which data; how to run analyses in SPSS for Windows and GLIM4; how to interpret results; and how to report and present the reports appropriately. Using a unified conceptual framework (based around the Generalized Linear Model) the authors explain the commonalities and relationships between methods that include both the analysis of categorical and continuous data.
Download or read book Introduction to Linear Regression Analysis written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2015-06-29 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Fourth Edition "As with previous editions, the authors have produced a leading textbook on regression." —Journal of the American Statistical Association A comprehensive and up-to-date introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The Fifth Edition features numerous newly added topics, including: A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models Regression models with random effects in addition to a discussion on subsampling and the importance of the mixed model Tests on individual regression coefficients and subsets of coefficients Examples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data. In addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material. Introduction to Linear Regression Analysis, Fifth Edition is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.
