Applied Regression Models In The Social Sciences

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Applied Regression Models In The Social Sciences
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Author : Dudley L. Poston
language : en
Publisher: Cambridge University Press
Release Date : 2023-08-17
Applied Regression Models In The Social Sciences written by Dudley L. Poston and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-17 with Social Science categories.
An accessible and practical guide to the use of applied regression models in testing and evaluating hypotheses dealing with social relationships, with example applications using relevant statistical methods in both Stata and R.
Regression Analysis For The Social Sciences
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Author : Rachel A. Gordon
language : en
Publisher: Routledge
Release Date : 2015-03-17
Regression Analysis For The Social Sciences written by Rachel A. Gordon and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-17 with Social Science categories.
Provides graduate students in the social sciences with the basic skills they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: •interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. •thorough integration of teaching statistical theory with teaching data processing and analysis. •teaching of Stata and use of chapter exercises in which students practice programming and interpretation on the same data set. A separate set of exercises allows students to select a data set to apply the concepts learned in each chapter to a research question of interest to them, all updated for this edition.
Applied Regression Analysis And Generalized Linear Models
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Author : John Fox
language : en
Publisher: SAGE Publications
Release Date : 2015-03-18
Applied Regression Analysis And Generalized Linear Models written by John Fox and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-18 with Social Science categories.
Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book. Accompanying website resources containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the author′s website. NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the author′s website.
Regression Analysis For Social Sciences
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Author : Alexander von Eye
language : en
Publisher: Elsevier
Release Date : 1998-08-12
Regression Analysis For Social Sciences written by Alexander von Eye and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-08-12 with Social Science categories.
Regression Analysis for Social Sciences presents methods of regression analysis in an accessible way, with each method having illustrations and examples. A broad spectrum of methods are included: multiple categorical predictors, methods for curvilinear regression, and methods for symmetric regression. This book can be used for courses in regression analysis at the advanced undergraduate and beginning graduate level in the social and behavioral sciences. Most of the techniques are explained step-by-step enabling students and researchers to analyze their own data. Examples include data from the social and behavioral sciences as well as biology, making the book useful for readers with biological and biometrical backgrounds. Sample command and result files for SYSTAT are included in the text. - Presents accessible methods of regression analysis - Includes a broad spectrum of methods - Techniques are explained step-by-step - Provides sample command and result files for SYSTAT
Applied Linear Statistical Models
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Author : Michael H. Kutner
language : en
Publisher: McGraw-Hill Education
Release Date : 2005
Applied Linear Statistical Models written by Michael H. Kutner and has been published by McGraw-Hill Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Analysis of variance categories.
Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.
Spatial Regression Models For The Social Sciences
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Author : Guangqing Chi
language : en
Publisher: SAGE Publications
Release Date : 2019-03-06
Spatial Regression Models For The Social Sciences written by Guangqing Chi and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-06 with Social Science categories.
Space and geography are important aspects of social science research in fields such as criminology, sociology, political science, and public health. Many social scientists are interested in the spatial clustering of various behaviors and events. There has been a rapid development of interest in regression methods for analyzing spatial data over recent years, but little available on the topic that is aimed at graduate students and advanced undergraduate classes in the social sciences (most texts are for the natural sciences, or regional science, or economics, and require a good understanding of advanced statistics and probability theory). Spatial Regression Models for the Social Sciences fills the gap, and focuses on the methods that are commonly used by social scientists. Each spatial regression method is introduced in the same way. Guangqing Chi and Jun Zhu explain what each method is and when and how to apply it, by connecting it to social science research topics. They try to avoid mathematical formulas and symbols as much as possible. Secondly, throughout the book they use the same social science example to demonstrate applications of each method and what the results can tell us. Spatial Regression Models for the Social Sciences provides comprehensive coverage of spatial regression methods for social scientists and introduces the methods in an easy-to-follow manner.
Data Analysis Using Regression And Multilevel Hierarchical Models
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Author : Andrew Gelman
language : en
Publisher: Cambridge University Press
Release Date : 2007
Data Analysis Using Regression And Multilevel Hierarchical Models written by Andrew Gelman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.
This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.
The Sage Handbook Of Regression Analysis And Causal Inference
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Author : Henning Best
language : en
Publisher: SAGE
Release Date : 2013-12-20
The Sage Handbook Of Regression Analysis And Causal Inference written by Henning Best and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-20 with Social Science categories.
′The editors of the new SAGE Handbook of Regression Analysis and Causal Inference have assembled a wide-ranging, high-quality, and timely collection of articles on topics of central importance to quantitative social research, many written by leaders in the field. Everyone engaged in statistical analysis of social-science data will find something of interest in this book.′ - John Fox, Professor, Department of Sociology, McMaster University ′The authors do a great job in explaining the various statistical methods in a clear and simple way - focussing on fundamental understanding, interpretation of results, and practical application - yet being precise in their exposition.′ - Ben Jann, Executive Director, Institute of Sociology, University of Bern ′Best and Wolf have put together a powerful collection, especially valuable in its separate discussions of uses for both cross-sectional and panel data analysis.′ -Tom Smith, Senior Fellow, NORC, University of Chicago Edited and written by a team of leading international social scientists, this Handbook provides a comprehensive introduction to multivariate methods. The Handbook focuses on regression analysis of cross-sectional and longitudinal data with an emphasis on causal analysis, thereby covering a large number of different techniques including selection models, complex samples, and regression discontinuities. Each Part starts with a non-mathematical introduction to the method covered in that section, giving readers a basic knowledge of the method’s logic, scope and unique features. Next, the mathematical and statistical basis of each method is presented along with advanced aspects. Using real-world data from the European Social Survey (ESS) and the Socio-Economic Panel (GSOEP), the book provides a comprehensive discussion of each method’s application, making this an ideal text for PhD students and researchers embarking on their own data analysis.
Time Series Analysis For The Social Sciences
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Author : Janet M. Box-Steffensmeier
language : en
Publisher: Cambridge University Press
Release Date : 2014-12-22
Time Series Analysis For The Social Sciences written by Janet M. Box-Steffensmeier and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-22 with Mathematics categories.
This book provides instruction and examples of the core methods in time series econometrics, drawing from several main fields of the social sciences.
Multilevel Analysis For Applied Research
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Author : Robert Bickel
language : en
Publisher: Guilford Press
Release Date : 2007-03-19
Multilevel Analysis For Applied Research written by Robert Bickel and has been published by Guilford Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-19 with Psychology categories.
This book provides a uniquely accessible introduction to multilevel modeling, a powerful tool for analyzing relationships between an individual-level dependent variable, such as student reading achievement, and individual-level and contextual explanatory factors, such as gender and neighborhood quality. Helping readers build on the statistical techniques they already know, Robert Bickel emphasizes the parallels with more familiar regression models, shows how to do multilevel modeling using SPSS, and demonstrates how to interpret the results. He discusses the strengths and limitations of multilevel analysis and explains specific circumstances in which it offers (or does not offer) methodological advantages over more traditional techniques. Over 300 dataset examples from research on educational achievement, income attainment, voting behavior, and other timely issues are presented in numbered procedural steps.