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This book introduces the reader to the main quantitative concepts, methods, and computational techniques needed for the development, evaluation, and application of tests in the behavioral/social sciences, including educational tests. Two empirical examples are carried throughout to illustrate alternative methods. Other data sets are used for special illustrations. Self-contained programs for confirmatory and exploratory factor analysis are available on the Web. Intended for students of psychology, particularly educational psychology, as well as social science students interested in how tests are constructed and used, prerequisites include a course on statistics. The programs and data files for this book can be downloaded from www.psypress.com/test-theory/
Factor Analysis is a genetic term for a somewhat vaguely delimited set of techniques for data processing, mainly applicable to the social and biological sciences. These techniques have been developed for the analysis of mutual relationships among a number of measurements made on a number of measurable entities. In the broad sense, factor analysis comprises a number of statistical models which yield testable hypotheses -- hypotheses that may confirm or disconfirm in terms of the usual statistical procedures for making tests of significance. It also comprises a number of simplifying procedures for the approximate description of data, which do not in any sense constitute disconfirmable hypothes...
Contemporary Psychometrics features cutting edge chapters organized in four sections: test theory, factor analysis, structural equation modeling, and multivariate analysis. The section on test theory includes topics such as multidimensional item response theory (IRT), the relationship between IRT and factor analysis, estimation and testing of these models, and basic measurement issues that are often neglected. The factor analysis section reviews the history and development of the model, factorial invariance and factor analysis indeterminacy, and Bayesian inference for factor scores and parameter estimates. The section on structural equation modeling (SEM) includes the general algebraic-graph...
Hayduk is equally at ease explaining the simplest and most advanced applications of the program . . . Hayduk has written more than just a solid text for use in advanced graduate courses on statistical modeling. Those with a firm mathematical background who wish to learn about the approach, or those who know a little about the program and want to know more, will find this an excellent reference.
A more appropriate Monte-Carlo-test model is proposed and a brief review of the recent literature is provided.
Item response theory has become an essential component in the toolkit of every researcher in the behavioral sciences. It provides a powerful means to study individual responses to a variety of stimuli, and the methodology has been extended and developed to cover many different models of interaction. This volume presents a wide-ranging handbook to item response theory - and its applications to educational and psychological testing. It will serve as both an introduction to the subject and also as a comprehensive reference volume for practitioners and researchers. It is organized into six major sections: the nominal categories model, models for response time or multiple attempts on items, model...
This book examines, in comparative perspective, the different ideals about family and society and how they have impacted on real family life across a number of countries in the Middle East.
Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial computer programs for performing factor analysis and structural equation modeling. This long-awaited e
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...
Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing path diagrams to explain the relationships in the models. This approach helps less mathematically-inclined readers to grasp the underlying relations among path analysis, factor analysis, and structural equation modeling, and to set up and carry out such analyses. This revised and expanded fifth edition again contains key chapters on path analysis, structural equation models, and exploratory factor analysis. In addition, it contains new material on composite reliability, models with categorical data, the minimum average partial procedure, bi-factor models, a...