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The Exploration for Guessing and Latent Ability in IRT Models

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Statistical Analysis of Questionnaires

, validity, and scaling as well as item response theory (IRT) fundamentals and IRT for dichotomous and polytomous items. The authors explore the;

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Statistical Analysis of Questionnaires

, validity, and scaling as well as item response theory (IRT) fundamentals and IRT for dichotomous and polytomous items. The authors explore the;

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Handbook of Item Response Theory Modeling

models are provided along with suggestions for deciding among the family of IRT models available. Each chapter provides an introduction;

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Handbook of Item Response Theory Modeling

models are provided along with suggestions for deciding among the family of IRT models available. Each chapter provides an introduction;

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Using R for Item Response Theory Model Applications

book provides practical line-by-line descriptions of how to use R IRT packages for various IRT models. The scope and coverage of the modeling;

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Using R for Item Response Theory Model Applications

book provides practical line-by-line descriptions of how to use R IRT packages for various IRT models. The scope and coverage of the modeling;

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Item Response Theory

used to estimate the item or ability parameters under various IRT models. Extensively revised and expanded, this edition offers three new;

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Item Response Theory

Theory, accomplished psychometricians Darrell Bock and Robert Gibbons deliver a comprehensive and up-to-date exploration of the theoretical;

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Handbook of Item Response Theory

all chapters. Each chapter is self-contained and deals with the latest developments in IRT.;

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Contemporary Psychometrics

modeling, and multivariate analysis. The section on test theory includes topics such as multidimensional item response theory (IRT), the;

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Contemporary Psychometrics

modeling, and multivariate analysis. The section on test theory includes topics such as multidimensional item response theory (IRT), the;

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An Introduction to Latent Class Analysis

latent classes, a latent class model approach for analyzing learning structures, the latent Markov analysis for longitudinal data, and path;

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Handbook of Item Response Theory: Three Volume Set

all chapters. Each chapter is self-contained and deals with the latest developments in IRT.;

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Handbook of Polytomous Item Response Theory Models

that cut across these models, and a common notation for calculating functions for each model. An introduction to IRT software is also provided;

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Educational Measurement for Applied Researchers

instruments. It focuses on the use of classical test theory (CTT) and item response theory (IRT), which are often required in the fields of psychology;

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Structural Equation Modeling

SEM models, and estimate sample size for latent class analysis (LCA) model. The statistical modeling program Mplus Version 8.2 is featured;

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Latent Markov Models for Longitudinal Data

discusses how the Markov chain model and the latent class model represent a useful paradigm for latent Markov models. The authors illustrate the;

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Latent Markov Models for Longitudinal Data

how the Markov chain model and the latent class model represent a useful paradigm for latent Markov models. The authors illustrate the;

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Item Response Theory

This book develops an intuitive understanding of IRT principles through the use of graphical displays and analogies to familiar;

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Fundamentals Of Item Response Theory

, test equating, and computerized-adaptive testing. The book also includes a thorough discussion of alternative procedures for estimating IRT;

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Handbook of Item Response Theory: Volume 2

presents classical and modern statistical tools used in item response theory (IRT). While IRT heavily depends on the use of statistical tools for;

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Handbook of Item Response

presents classical and modern statistical tools used in item response theory (IRT). While IRT heavily depends on the use of statistical tools for;

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Latent Variable Models and Factor Analysis

numerical examples. Nature and interpretation of a latent variable is also introduced along with related techniques for investigating dependency;

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Semialgebraic Statistics and Latent Tree Models

the local and global geometry of latent tree models. It also extends previous results to Gaussian latent tree models. This book shows;

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Semialgebraic Statistics and Latent Tree Models

the local and global geometry of latent tree models. It also extends previous results to Gaussian latent tree models. This book shows;

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Latent Variable Models

analyses with their own data. The book and accompanying website provide all of the data for the book's examples as well as syntax from latent;

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