Interpreting and Using Regression

Interpreting and Using Regression PDF Author: Christopher H. Achen
Publisher: SAGE
ISBN: 9780803919150
Category : Mathematics
Languages : en
Pages : 92

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Book Description
Interpreting and Using Regression sets out the actual procedures researchers employ, places them in the framework of statistical theory, and shows how good research takes account both of statistical theory and real world demands. Achen builds a working philosophy of regression that goes well beyond the abstract, unrealistic treatment given in previous texts.

Interpreting and Using Regression

Interpreting and Using Regression PDF Author: Christopher H. Achen
Publisher: SAGE
ISBN: 9780803919150
Category : Mathematics
Languages : en
Pages : 92

Get Book Here

Book Description
Interpreting and Using Regression sets out the actual procedures researchers employ, places them in the framework of statistical theory, and shows how good research takes account both of statistical theory and real world demands. Achen builds a working philosophy of regression that goes well beyond the abstract, unrealistic treatment given in previous texts.

Interpreting and Using Regression

Interpreting and Using Regression PDF Author: Christopher H. Achen
Publisher: SAGE Publications, Incorporated
ISBN: 9780803919150
Category : Social Science
Languages : en
Pages : 0

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Book Description
Interpreting and Using Regression sets out the actual procedures researchers employ, places them in the framework of statistical theory, and shows how good research takes account both of statistical theory and real world demands. Achen builds a working philosophy of regression that goes well beyond the abstract, unrealistic treatment given in previous texts.

Multiple Regression

Multiple Regression PDF Author: Leona S. Aiken
Publisher: SAGE
ISBN: 9780761907121
Category : Business & Economics
Languages : en
Pages : 228

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Book Description
This successful book, now available in paperback, provides academics and researchers with a clear set of prescriptions for estimating, testing and probing interactions in regression models. Including the latest research in the area, such as Fuller's work on the corrected/constrained estimator, the book is appropriate for anyone who uses multiple regression to estimate models, or for those enrolled in courses on multivariate statistics.

Modeling and Interpreting Interactive Hypotheses in Regression Analysis

Modeling and Interpreting Interactive Hypotheses in Regression Analysis PDF Author: Robert Franzese
Publisher: University of Michigan Press
ISBN: 0472022997
Category : Political Science
Languages : en
Pages : 164

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Book Description
Social scientists study complex phenomena about which they often propose intricate hypotheses tested with linear-interactive or multiplicative terms. While interaction terms are hardly new to social science research, researchers have yet to develop a common methodology for using and interpreting them. Modeling and Interpreting Interactive Hypotheses in Regression Analysis provides step-by-step guidance on how to connect substantive theories to statistical models and how to interpret and present the results. "Kam and Franzese is a must-have for all empirical social scientists interested in teasing out the complexities of their data." ---Janet M. Box-Steffensmeier, Ohio State University "Kam and Franzese have written what will become the definitive source on dealing with interaction terms and testing interactive hypotheses. It will serve as the standard reference for political scientists and will be one of those books that everyone will turn to when helping our students or doing our work. But more than that, this book is the best text I have seen for getting students to really think about the importance of careful specification and testing of their hypotheses." ---David A. M. Peterson, Texas A&M University "Kam and Franzese have given scholars and teachers of regression models something they've needed for years: a clear, concise guide to understanding multiplicative interactions. Motivated by real substantive examples and packed with valuable examples and graphs, their book belongs on the shelf of every working social scientist." ---Christopher Zorn, University of South Carolina "Kam and Franzese make it easy to model what good researchers have known for a long time: many important and interesting causal effects depend on the presence of other conditions. Their book shows how to explore interactive hypotheses in your own research and how to present your results. The book is straightforward yet technically sophisticated. There are no more excuses for misunderstanding, misrepresenting, or simply missing out on interaction effects!" ---Andrew Gould, University of Notre Dame Cindy D. Kam is Assistant Professor, Department of Political Science, University of California, Davis. Robert J. Franzese Jr. is Associate Professor, Department of Political Science, University of Michigan, and Research Associate Professor, Center for Political Studies, Institute for Social Research, University of Michigan. For datasets, syntax, and worksheets to help readers work through the examples covered in the book, visit: www.press.umich.edu/KamFranzese/Interactions.html

Applied Regression Analysis

Applied Regression Analysis PDF Author: Christer Thrane
Publisher: Routledge
ISBN: 0429813023
Category : Business & Economics
Languages : en
Pages : 285

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Book Description
This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data. Contrary to other textbooks on regression, this book is based on the idea that you do not necessarily need to know much about statistics and mathematics to get a firm grip on regression and perform it to perfection. This non-technical point of departure is complemented by practical examples of real-life data analysis using statistics software such as Stata, R and SPSS. Parts 1 and 2 of the book cover the basics, such as simple linear regression, multiple linear regression, how to interpret the output from statistics programs, significance testing and the key regression assumptions. Part 3 deals with how to practically handle violations of the classical linear regression assumptions, regression modeling for categorical y-variables and instrumental variable (IV) regression. Part 4 puts the various purposes of, or motivations for, regression into the wider context of writing a scholarly report and points to some extensions to related statistical techniques. This book is written primarily for those who need to do regression analysis in practice, and not only to understand how this method works in theory. The book’s accessible approach is recommended for students from across the social sciences.

Interpreting and Using Statistics in Psychological Research

Interpreting and Using Statistics in Psychological Research PDF Author: Andrew N. Christopher
Publisher: SAGE Publications
ISBN: 150630415X
Category : Psychology
Languages : en
Pages : 585

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Book Description
This practical, conceptual introduction to statistical analysis by award-winning teacher Andrew N. Christopher uses published research with inherently interesting social sciences content to help students make clear connections between statistics and real life. Using a friendly, easy-to-understand presentation, Christopher walks students through the hand calculations of key statistical tools and provides step-by-step instructions on how to run the appropriate analyses for each type of statistic in SPSS and how to interpret the output. With the premise that a conceptual grasp of statistical techniques is critical for students to truly understand why they are doing what they are doing, the author avoids overly formulaic jargon and instead focuses on when and how to use statistical techniques appropriately.

Data Analysis Using Regression and Multilevel/Hierarchical Models

Data Analysis Using Regression and Multilevel/Hierarchical Models PDF Author: Andrew Gelman
Publisher: Cambridge University Press
ISBN: 9780521686891
Category : Mathematics
Languages : en
Pages : 654

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Book Description
This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Understanding Regression Analysis

Understanding Regression Analysis PDF Author: Larry D. Schroeder
Publisher: SAGE
ISBN: 9780803927582
Category : Social Science
Languages : en
Pages : 100

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Book Description
Providing beginners with a background to the frequently-used technique of linear regression, this text provides a heuristic explanation of the procedures and terms used in regression analysis and has been written at the most elementary level.

Regression Analysis

Regression Analysis PDF Author: Jim Frost
Publisher: Statistics By Jim Publishing
ISBN: 9781735431185
Category :
Languages : en
Pages : 352

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Book Description
Intuitively understand regression analysis by focusing on concepts and graphs rather than equations and formulas. I use everyday language so you can grasp regression at a deeper level. Progress from a beginner to a skilled practitioner. Learn practical tips for performing your analysis and interpreting the results. Feel confident that you're analyzing your data properly and able to trust your results. Know that you can detect and correct problems that arise. Includes access to free downloadable datasets for the examples. Learn the following: How regression works and when to use it. Selecting the correct type of regression analysis. Specifying the best model. Understanding main effects, interaction effects, and modeling curvature. Interpreting the results. Assessing the fit of the model. Generating predictions and evaluating their precision. Checking the assumptions and resolving issues. Examples of different types of regression analyses.

Applied Logistic Regression Analysis

Applied Logistic Regression Analysis PDF Author: Scott Menard
Publisher: SAGE
ISBN: 9780761922087
Category : Mathematics
Languages : en
Pages : 130

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Book Description
The 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.