Lisrel Approaches To Interaction Effects In Multiple Regression
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Lisrel Approaches To Interaction Effects In Multiple Regression
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Author : James Jaccard
language : en
Publisher: SAGE
Release Date : 1996-03-21
Lisrel Approaches To Interaction Effects In Multiple Regression written by James Jaccard and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-03-21 with Mathematics categories.
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.
Interaction And Nonlinear Effects In Structural Equation Modeling
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Author : Randall E. Schumacker
language : en
Publisher: Routledge
Release Date : 2017-07-05
Interaction And Nonlinear Effects In Structural Equation Modeling written by Randall E. Schumacker and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-05 with Psychology categories.
This volume provides a comprehensive presentation of the various procedures currently available for testing interaction and nonlinear effects in structural equation modeling. By focusing on various software applications, the reader should quickly be able to incorporate one of the procedures into testing interaction or nonlinear effects in their own model. Although every attempt is made to keep mathematical details to a minimum, it is assumed that the reader has mastered the equivalent of a graduate-level multivariate statistics course which includes adequate coverage of structural equation modeling. This book will be of interest to researchers and practitioners in education and the social sciences.
Interaction Effects In Linear And Generalized Linear Models
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Author : Robert L. Kaufman
language : en
Publisher: SAGE Publications
Release Date : 2018-09-06
Interaction Effects In Linear And Generalized Linear Models written by Robert L. Kaufman and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-06 with Social Science categories.
"This book is remarkable in its accessible treatment of interaction effects. Although this concept can be challenging for students (even those with some background in statistics), this book presents the material in a very accessible manner, with plenty of examples to help the reader understand how to interpret their results." –Nicole Kalaf-Hughes, Bowling Green State University 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, 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 author’s website provides a downloadable toolkit of Stata® routines to produce the calculations, tables, and graphics for each interpretive tool discussed. Also available are the Stata® dataset files to run the examples in the book.
An Introduction To Exponential Random Graph Modeling
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Author : Jenine K. Harris
language : en
Publisher: SAGE Publications
Release Date : 2013-12-23
An Introduction To Exponential Random Graph Modeling written by Jenine K. Harris and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-23 with Social Science categories.
This volume introduces the basic concepts of Exponential Random Graph Modeling (ERGM), gives examples of why it is used, and shows the reader how to conduct basic ERGM analyses in their own research. ERGM is a statistical approach to modeling social network structure that goes beyond the descriptive methods conventionally used in social network analysis. Although it was developed to handle the inherent non-independence of network data, the results of ERGM are interpreted in similar ways to logistic regression, making this a very useful method for examining social systems. Recent advances in statistical software have helped make ERGM accessible to social scientists, but a concise guide to using ERGM has been lacking. An Introduction to Exponential Random Graph Modeling, by Jenine K. Harris, fills that gap, by using examples from public health, and walking the reader through the process of ERGM model-building using R statistical software and the statnet package.
Factor Analysis At 100
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Author : Robert Cudeck
language : en
Publisher: Routledge
Release Date : 2007-03-06
Factor Analysis At 100 written by Robert Cudeck and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-03-06 with Business & Economics categories.
This book provides a retrospective look at major developments as well as a prospective view of future directions in factor analysis. In so doing, it demonstrates how and why factor analysis is considered to be one of the methodological pillars of behavioral research. Featuring an outstanding collection of contributors, this volume offers unique insights on factor analysis and its related methods. The book reviews some of the extensions of factor analysis to such techniques as latent growth curve models, models for categorical data, and structural equation models. Intended for graduate students and researchers in the behavioral, social, health, and biological sciences who use this technique in their research, a basic knowledge of factor analysis is required and a working knowledge of linear algebra is helpful.
Confirmatory Factor Analysis
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Author : J. Micah Roos
language : en
Publisher: SAGE Publications
Release Date : 2021-10-19
Confirmatory Factor Analysis written by J. Micah Roos and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-19 with Social Science categories.
Measurement connects theoretical concepts to what is observable in the empirical world, and is fundamental to all social and behavioral research. In this volume, J. Micah Roos and Shawn Bauldry introduce a popular approach to measurement: Confirmatory Factor Analysis (CFA). As the authors explain, CFA is a theoretically informed statistical framework for linking multiple observed variables to latent variables that are not directly measurable. The authors begin by defining terms, introducing notation, and illustrating a wide variety of measurement models with different relationships between latent and observed variables. They proceed to a thorough treatment of model estimation, followed by a discussion of model fit. Most of the volume focuses on measures that approximate continuous variables, but the authors also devote a chapter to categorical indicators. Each chapter develops a different example (sometimes two) covering topics as diverse as racist attitudes, theological conservatism, leadership qualities, psychological distress, self-efficacy, beliefs about democracy, and Christian nationalism drawn mainly from national surveys. Data to replicate the examples are available on a companion website, along with code for R, Stata, and Mplus.
Sequence Analysis
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Author : Marcel Raab
language : en
Publisher: SAGE Publications
Release Date : 2022-04-11
Sequence Analysis written by Marcel Raab and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-11 with Social Science categories.
Sequence analysis (SA) was developed to study social processes that unfold over time as sequences of events. It has gained increasing attention as the availability of longitudinal data made it possible to address sequence-oriented questions. This volume introduces the basics of SA to guide practitioners and support instructors through the basic workflow of sequence analysis. In addition to the basics, this book outlines recent advances and innovations in SA. The presentation of statistical, substantive, and theoretical foundations is enriched by examples to help the reader understand the repercussions of specific analytical choices. The extensive ancillary material supports self-learning based on real-world survey data and research questions from the field of life course research. Data and code and a variety of additional resources to enrich the use of this book are available on an accompanying website.
Applied Bayesian Statistics
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Author : Scott M. Lynch
language : en
Publisher: SAGE Publications
Release Date : 2022-10-31
Applied Bayesian Statistics written by Scott M. Lynch and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-31 with Social Science categories.
Bayesian statistical analyses have become increasingly common over the last two decades. The rapid increase in computing power that facilitated their implementation coincided with major changes in the research interests of, and data availability for, social scientists. Specifically, the last two decades have seen an increase in the availability of panel data sets, other hierarchically structured data sets including spatially organized data, along with interests in life course processes and the influence of context on individual behavior and outcomes. The Bayesian approach to statistics is well-suited for these types of data and research questions. Applied Bayesian Statistics is an introduction to these methods that is geared toward social scientists. Author Scott M. Lynch makes the material accessible by emphasizing application more than theory, explaining the math in a step-by-step fashion, and demonstrating the Bayesian approach in analyses of U.S. political trends drawing on data from the General Social Survey.
Multilevel Structural Equation Modeling
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Author : Bruno Castanho Silva
language : en
Publisher: SAGE Publications
Release Date : 2019-02-28
Multilevel Structural Equation Modeling written by Bruno Castanho Silva and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-28 with Social Science categories.
Multilevel Structural Equation Modeling serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the social sciences. As the first book of its kind, this title is an accessible, hands-on introduction for beginners of the topic. The authors predict a growth in this area, fueled by both data availability and also the availability of new and improved software to run these models. The applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra guarantee that this volume will be useful to social science graduate students wanting to utilize such models.
Multilevel Modeling
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Author : Douglas A. Luke
language : en
Publisher: SAGE Publications
Release Date : 2019-12-13
Multilevel Modeling written by Douglas A. Luke and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-13 with Social Science categories.
Multilevel Modeling is a concise, practical guide to building models for multilevel and longitudinal data. Author Douglas A. Luke begins by providing a rationale for multilevel models; outlines the basic approach to estimating and evaluating a two-level model; discusses the major extensions to mixed-effects models; and provides advice for where to go for instruction in more advanced techniques. Rich with examples, the Second Edition expands coverage of longitudinal methods, diagnostic procedures, models of counts (Poisson), power analysis, cross-classified models, and adds a new section added on presenting modeling results. A website for the book includes the data and the statistical code (both R and Stata) used for all of the presented analyses.