interpreting and using regression

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Interpreting And Using Regression

Author : Christopher H. Achen
ISBN : 0803919158
Genre : Mathematics
File Size : 89. 65 MB
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Outlines 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. Learn more about "The Little Green Book" - QASS Series! Click Here

Interpreting And Using Regression

Author : Christopher H. Achen
ISBN : 0803919158
Genre : Mathematics
File Size : 39. 40 MB
Format : PDF, ePub
Download : 486
Read : 287

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Outlines 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. Learn more about "The Little Green Book" - QASS Series! Click Here

Interpreting And Using Statistics In Psychological Research

Author : Andrew N. Christopher
ISBN : 9781506304182
Genre : Psychology
File Size : 84. 9 MB
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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.

Modeling And Interpreting Interactive Hypotheses In Regression Analysis

Author : Robert Franzese
ISBN : 0472022997
Genre : Political Science
File Size : 51. 35 MB
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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

Interpreting And Visualizing Regression Models Using Stata

Author : Michael N. Mitchell
ISBN : 1597181072
Genre : Mathematics
File Size : 88. 58 MB
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Michael Mitchell's Interpreting and Visualizing Regression Models Using Stata is a clear treatment of how to carefully present results from model-fitting in a wide variety of settings. It is a boon to anyone who has to present the tangible meaning of a complex model in a clear fashion, regardless of the audience. As an example, many experienced researchers start to squirm when asked to give a simple explanation of the applied meaning of interactions in nonlinear models such as logistic regression. The tools in Mitchell's book make this task much more enjoyable and comprehensible. Mitchell starts with simple linear regression (which is simple in all ways), and then adds polynomials and discontinuities. This is followed by 2-way and 3-way interaction until interpretation of coefficients through words is difficult. By careful use of Stata's marginsplot command, Mitchell shows how well graphs can be used to show effects. He also includes careful verbal interpretation of coefficients to make communications complete. He then extends the methods from linear regression to various types of nonlinear regression, such as multilevel or survival models. A significant difference between this book and most others on regression models is that Mitchell spends quite some time on fitting and visualizing discontinuous models' models where the outcome can change value suddenly at thresholds. Such models are natural in settings such as education and policy evaluation, where graduation or policy changes can make sudden changes in income or revenue. This book is a worthwhile addition to the library of anyone involved in statistical consulting, teaching, or collaborative applied statistical environments.

Multiple Regression

Author : Leona S. Aiken
ISBN : 0761907122
Genre : Business & Economics
File Size : 26. 80 MB
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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.

Regression Analysis For Categorical Moderators

Author : Herman Aguinis
ISBN : 1572309695
Genre : Social Science
File Size : 37. 81 MB
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Does the stability of personality vary by gender or ethnicity? Does a particular therapy work better to treat clients with one type of personality disorder than those with another? Providing a solution to thorny problems such as these, Aguinis shows readers how to better assess whether the relationship between two variables is moderated by group membership through the use of a statistical technique, moderated multiple regression (MMR). Clearly written, the book requires only basic knowledge of inferential statistics. It helps students, researchers, and practitioners determine whether a particular intervention is likely to yield dissimilar outcomes for members of various groups. Associated computer programs and data sets are available at the author's website (http: //mypage.iu.edu/ haguinis/mmr).

Using And Interpreting Statistics In The Social Behavioral And Health Sciences

Author : William E. Wagner, III
ISBN : 9781544321103
Genre : Social Science
File Size : 24. 98 MB
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Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences by William E. Wagner, III and Brian J. Gillespie is designed to be paired with any undergraduate introduction to research methods text used by students in a variety of disciplines. It introduces students to statistics at the conceptual level—examining the meaning of statistics, and why researchers use a particular statistical technique, rather than computational skills. Focusing on descriptive statistics, and some more advanced topics such as tests of significance, measures of association, and regression analysis, this brief, inexpensive text is the perfect companion to help students who have not yet taken an introductory statistics course or are confused by the statistics used in the articles they are reading.

Regression Analysis

Author : Richard A. Berk
ISBN : 9781452244860
Genre : Social Science
File Size : 22. 46 MB
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Regression Analysis: A Constructive Critique identifies a wide variety of problems with regression analysis as it is commonly used and then provides a number of ways in which practice could be improved. Regression is most useful for data reduction, leading to relatively simple but rich and precise descriptions of patterns in a data set. The emphasis on description provides readers with an insightful rethinking from the ground up of what regression analysis can do, so that readers can better match regression analysis with useful empirical questions and improved policy-related research. "An interesting and lively text, rich in practical wisdom, written for people who do empirical work in the social sciences and their graduate students." --David A. Freedman, Professor of Statistics, University of California, Berkeley

Interaction Effects In Logistic Regression

Author : James Jaccard
ISBN : 0761922075
Genre : Mathematics
File Size : 90. 92 MB
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This book provides an introduction to the analysis of interaction effects in logistic regression by focusing on the interpretation of the coefficients of interactive logistic models for a wide range of situations encountered in the research literature. The volume is oriented toward the applied researcher with a rudimentary background in multiple regression and logistic regression and does not include complex formulas that could be intimidating to the applied researcher.

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