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Higher-Order Growth Curves and Mixture Modeling with Mplus
This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth cu...
Longitudinal Structural Equation Modeling
Longitudinal Structural Equation Modeling is a comprehensive resource that reviews structural equation modeling (SEM) strategies for longitudinal data to help readers determine which modeling options are available for which hypotheses. This accessibly written book explores a range of models, from basic to sophisticated, including the statistical and conceptual underpinnings that are the building blocks of the analyses. By exploring connections between models, it demonstrates how SEM is related to other longitudinal data techniques and shows when to choose one analysis over another. Newsom emphasizes concepts and practical guidance for applied research rather than focusing on mathematical pro...
What If There Were No Significance Tests?
The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways. Other options (data visualization, replication or meta-analysis), other features (mediation, moderation, multiple levels or classes), and other approaches (Bayesian analysis, simulation, data mining, qualitative inquiry) are also suggested. The Classic Edition’s new Introduction demonstrates the ongoing relevance of the topic and the charge to move away from an exclusive focus on NHST, along with new methods to help m...
Aging and the Life Course
Aging & the Life Course: Social & Cultural Contexts provides an accessible, up-to-date introduction to the study of aging and the life course from a distinctly sociological perspective. It explores the sociocultural dimensions of aging while encouraging critical thinking about the diversity of aging experiences, societal attitudes toward older adults, the politics and economics of growing old, and end-of-life resources. Throughout the text, Deborah Lowry emphasizes the relevance of the material for working with older populations, understanding social policy and policy debates, improving communities, relating to others, and understanding ourselves. Organized into four major sections, Part I introduces students to fundamental demographic, sociological, and life course concepts; part II explores the experiences and conditions of aging, especially in particular groups; and part III presents current research on older adults’ engagement in work, family, social networks, and sex. Finally, Part IV addresses themes of aging and social change.
Categorical and Nonparametric Data Analysis
Now in its second edition, this book provides a focused, comprehensive overview of both categorical and nonparametric statistics, offering a conceptual framework for choosing the most appropriate test in various scenarios. The book’s clear explanations and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of these techniques. Basic statistics and probability are reviewed for those needing a refresher with mathematical derivations placed in optional appendices. Highlights include the following: • Three chapters co-authored with Edgar Brunner address modern nonparametric techniques, along with accompanying R code. â...
Structural Equation Modeling With AMOS
This bestselling text provides a practical guide to structural equation modeling (SEM) using the Amos Graphical approach. Using clear, everyday language, the text is ideal for those with little to no exposure to either SEM or Amos. The author reviews SEM applications based on actual data taken from her own research. Each chapter "walks" readers through the steps involved (specification, estimation, evaluation, and post hoc modification) in testing a variety of SEM models. Accompanying each application is: an explanation of the issues addressed and a schematic presentation of hypothesized model structure; Amos input and output with interpretations; use of the Amos toolbar icons and pull-down ...
The Essence of Multivariate Thinking
Focusing on the underlying themes that run through most multivariate methods, in this fully updated 3rd edition of The Essence of Multivariate Thinking Dr. Harlow shares the similarities and differences among multiple multivariate methods to help ease the understanding of the basic concepts. The book continues to highlight the main themes that run through just about every quantitative method, describing the statistical features in clear language. Analyzed examples are presented in 12 of the 15 chapters, showing when and how to use relevant multivariate methods, and how to interpret the findings both from an overarching macro- and more specific micro-level approach that includes focus on stat...
Introduction to Item Response Theory Models and Applications
This is a highly accessible, comprehensive introduction to item response theory (IRT) models and their use in various aspects of assessment/testing. The book employs a mixture of graphics and simulated data sets to ease the reader into the material and covers the basics required to obtain a solid grounding in IRT. Written in an easily accessible way that assumes little mathematical knowledge, Carlson presents detailed descriptions of several commonly used IRT models, including those for items scored on a two-point (dichotomous) scale such as correct/incorrect, and those scored on multiple-point (polytomous) scales, such as degrees of correctness. One chapter describes a model in-depth and is followed by a chapter of instructions and illustrations showing how to apply the models to the reader’s own work. This book is an essential text for instructors and higher level undergraduate and postgraduate students of statistics, psychometrics, and measurement theory across the behavioral and social sciences, as well as testing professionals.
