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Interaction Effects In Multiple Regression

Author : James Jaccard
ISBN : 0761927425
Genre : Mathematics
File Size : 65.6 MB
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Interaction Effects in Multiple Regression has provided students and researchers with a readable and practical introduction to conducting analyses of interaction effects in the context of multiple regression. The new addition will expand the coverage on the analysis of three way interactions in multiple regression analysis. Learn more about "The Little Green Book" - QASS Series! Click Here
Category: Mathematics

Lisrel Approaches To Interaction Effects In Multiple Regression

Author : James Jaccard
ISBN : 0803971796
Genre : Social Science
File Size : 61.13 MB
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With detailed examples, this book demonstrates the use of the computer program LISREL and how it can be applied to the analysis of interactions in regression frameworks. The authors consider a wide range of applications including: qualitative moderator variables; longitudinal designs; and product term analysis. They describe different types of measurement error and then present a discussion of latent variable representations of measurement error which serves as the foundation for the analyses described in later chapters. Finally they offer a brief introduction to LISREL and show how it can be used to execute the analyses. Readers can use this book without any prior training in LISREL and will find it an excellent introduction to analytic methods that deal with the problem of measurement error in the analysis of interactions.
Category: Social Science

Multiple Regression

Author : Leona S. Aiken
ISBN : 0761907122
Genre : Business & Economics
File Size : 53.64 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.
Category: Business & Economics

Interaction Effects In Logistic Regression

Author : James Jaccard
ISBN : 0761922075
Genre : Social Science
File Size : 65.80 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.Learn more about "The Little Green Book" - QASS Series! Click Here
Category: Social Science

Learn About Multiple Regression With Interactions Between Categorical Variables In Survey Data In Stata With Data From The European Social Survey 2016

Author : Abigail-Kate Reid
ISBN : 1526480719
Genre : Economics
File Size : 83.61 MB
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This SAGE Research Methods Dataset example introduces readers to interaction effects in multiple regression. Multiple regression techniques allow researchers to evaluate whether a continuous dependent variable is a linear function of two or more independent variables. This example demonstrates how to compute and interpret product-term interactions between two categorical variables in Ordinary Least Squares (OLS) regression using a subset of data from the 2016 European Social Survey. Specifically, we test whether satisfaction with the economy is related to gender and whether respondents voted in the last national election. In this example, readers are introduced to the basic theory and assumptions underlying this technique, the type of question this technique can be used to answer, and how to produce and report results. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for Stata.
Category: Economics

Interaction Effects In Linear And Generalized Linear Models

Author : Robert L. Kaufman
ISBN : 9781506365398
Genre : Social Science
File Size : 30.46 MB
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Offering a clear set of workable examples with data and explanations, Interaction Effects in Linear and Generalized Linear Models is a comprehensive and accessible text that provides a unified approach to interpreting interaction effects. The book develops the statistical basis for the general principles of interpretive tools and applies them to a variety of examples, introduces the ICALC Toolkit for Stata (downloadable from the Robert L. Kaufman’s website), and offers a series of start-to-finish application examples to show students how to interpret interaction effects for a variety of different techniques of analysis, beginning with OLS regression. The data sets and the Stata code to reproduce the results of the application examples are available online.
Category: Social Science

Regression Analysis And Linear Models

Author : Richard B. Darlington
ISBN : 9781462521135
Genre : Social Science
File Size : 90.35 MB
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Ephasizing 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 ( 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.
Category: Social Science

Multilevel Analysis

Author : J. J. Hox
ISBN : 9780805832181
Genre : Mathematics
File Size : 45.50 MB
Format : PDF
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This volume provides an introduction to multilevel analysis for applied researchers. The book presents two types of multilevel models: the multilevel regression model; and a model for multilevel covariance structures.
Category: Mathematics

Handbook Of Data Analysis

Author : Professor Melissa A Hardy
ISBN : 0761966528
Genre : Social Science
File Size : 76.92 MB
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This text provides a reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference.
Category: Social Science

Regression With Dummy Variables

Author : Melissa A. Hardy
ISBN : 0803951280
Genre : Social Science
File Size : 40.68 MB
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It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behavior, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression.
Category: Social Science