This new text provides the most current coverage of measurement and psychometrics in a single volume. Authors W. Holmes Finch and Brian F. French first review the basics of psychometrics and measurement, before moving on to more complex topics such as equating and scaling, item response theory, standard setting, and computer adaptive testing. Also included are discussions of cutting-edge topics utilized by practitioners in the field, such as automated test development, game-based assessment, and automated test scoring. This book is ideal for use as a primary text for graduate-level psychometrics/measurement courses, as well as for researchers in need of a broad resource for understanding test theory. Features: "How it Works" and "Psychometrics in the Real World" boxes break down important concepts through worked examples, and show how theory can be applied to practice. End-of-chapter exercises allow students to test their comprehension of the material, while suggested readings and website links provide resources for further investigation. A collection of free online resources include the full output from R, SPSS, and Excel for each of the analyses conducted in the book, as well as additional exercises, sample homework assignments, answer keys, and PowerPoint lecture slides.

This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand the models and interpret the results. Every R command necessary for conducting the analyses is described along with the resulting output which provides readers with a template to follow when they apply the methods to their own data. The basic information pertinent to each model, the newest developments in these areas, and the relevant R code to use them are reviewed. Each chapter also features an introduction, summary, and suggested readings. A glossary of the text's boldfaced key terms and key R commands serve as helpful resources. The book is accompanied by a website with exercises, an answer key, and the in-text example data sets. Latent Variable Modeling with R: -Provides some examples that use messy data providing a more realistic situation readers will encounter with their own data. -Reviews a wide range of LVMs including factor analysis, structural equation modeling, item response theory, and mixture models and advanced topics such as fitting nonlinear structural equation models, nonparametric item response theory models, and mixture regression models. -Demonstrates how data simulation can help researchers better understand statistical methods and assist in selecting the necessary sample size prior to collecting data. -www.routledge.com/9780415832458 provides exercises that apply the models along with annotated R output answer keys and the data that corresponds to the in-text examples so readers can replicate the results and check their work. The book opens with basic instructions in how to use R to read data, download functions, and conduct basic analyses. From there, each chapter is dedicated to a different latent variable model including exploratory and confirmatory factor analysis (CFA), structural equation modeling (SEM), multiple groups CFA/SEM, least squares estimation, growth curve models, mixture models, item response theory (both dichotomous and polytomous items), differential item functioning (DIF), and correspondance analysis. The book concludes with a discussion of how data simulation can be used to better understand the workings of a statistical method and assist researchers in deciding on the necessary sample size prior to collecting data. A mixture of independently developed R code along with available libraries for simulating latent models in R are provided so readers can use these simulations to analyze data using the methods introduced in the previous chapters. Intended for use in graduate or advanced undergraduate courses in latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, and social and health sciences, researchers in these fields also appreciate this book's practical approach. The book provides sufficient conceptual background information to serve as a standalone text. Familiarity with basic statistical concepts is assumed but basic knowledge of R is not.

This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand the models and interpret the results. Every R command necessary for conducting the analyses is described along with the resulting output which provides readers with a template to follow when they apply the methods to their own data. The basic information pertinent to each model, the newest developments in these areas, and the relevant R code to use them are reviewed. Each chapter also features an introduction, summary, and suggested readings. A glossary of the text's boldfaced key terms and key R commands serve as helpful resources. The book is accompanied by a website with exercises, an answer key, and the in-text example data sets. Latent Variable Modeling with R: -Provides some examples that use messy data providing a more realistic situation readers will encounter with their own data. -Reviews a wide range of LVMs including factor analysis, structural equation modeling, item response theory, and mixture models and advanced topics such as fitting nonlinear structural equation models, nonparametric item response theory models, and mixture regression models. -Demonstrates how data simulation can help researchers better understand statistical methods and assist in selecting the necessary sample size prior to collecting data. -www.routledge.com/9780415832458 provides exercises that apply the models along with annotated R output answer keys and the data that corresponds to the in-text examples so readers can replicate the results and check their work. The book opens with basic instructions in how to use R to read data, download functions, and conduct basic analyses. From there, each chapter is dedicated to a different latent variable model including exploratory and confirmatory factor analysis (CFA), structural equation modeling (SEM), multiple groups CFA/SEM, least squares estimation, growth curve models, mixture models, item response theory (both dichotomous and polytomous items), differential item functioning (DIF), and correspondance analysis. The book concludes with a discussion of how data simulation can be used to better understand the workings of a statistical method and assist researchers in deciding on the necessary sample size prior to collecting data. A mixture of independently developed R code along with available libraries for simulating latent models in R are provided so readers can use these simulations to analyze data using the methods introduced in the previous chapters. Intended for use in graduate or advanced undergraduate courses in latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, and social and health sciences, researchers in these fields also appreciate this book's practical approach. The book provides sufficient conceptual background information to serve as a standalone text. Familiarity with basic statistical concepts is assumed but basic knowledge of R is not.

This new text provides the most current coverage of measurement and psychometrics in a single volume. Authors W. Holmes Finch and Brian F. French first review the basics of psychometrics and measurement, before moving on to more complex topics such as equating and scaling, item response theory, standard setting, and computer adaptive testing. Also included are discussions of cutting-edge topics utilized by practitioners in the field, such as automated test development, game-based assessment, and automated test scoring. This book is ideal for use as a primary text for graduate-level psychometrics/measurement courses, as well as for researchers in need of a broad resource for understanding test theory. Features: "How it Works" and "Psychometrics in the Real World" boxes break down important concepts through worked examples, and show how theory can be applied to practice. End-of-chapter exercises allow students to test their comprehension of the material, while suggested readings and website links provide resources for further investigation. A collection of free online resources include the full output from R, SPSS, and Excel for each of the analyses conducted in the book, as well as additional exercises, sample homework assignments, answer keys, and PowerPoint lecture slides.

El objetivo del libro es proporcionar a los lectores las herramientas necesarias para evaluar la calidad psicome trica de las medidas educativas y psicolo gicas, asi como de encuestas y cuestionarios. Cada capi tulo aborda un tema relativo a la pra ctica psicome trica y de la medida, con e nfasis en la aplicacio n. Los temas sera n tratados brevemente desde una perspectiva teo rica/te cnica con el fin de proporcionar al lector los antecedentes necesarios para utilizar e interpretar correctamente los ana lisis estadi sticos que se presentara n con posteriormente. Este libro esta dirigido a investigadores, profesionales y estudiantes de posgrado (Ma ster y Doctorado) que buscan una gui a para realizar ana lisis psicome tricos de diferentes instrumentos de evaluacio n. Asumimos un nivel ba sico de conocimientos estadi sticos, pero estos conceptos se ira n repasando a lo largo de los diferentes capi tulos. Nos imaginamos que este texto (a) esperara pacientemente en algunos despachos implorando ser entregado, como recurso, a un estudiante, (b) tendra un lugar fijo en las mesas de los despachos donde continuamente, y debido a su uso diario, sera el primero del monto n, (c) estara en las mochilas de los estudiantes de postgrado, y los acompan ara felizmente desde casa al trabajo o a las clases y vuelta, (d) aparecera orgullosamente como un texto de referencia en los programas y guia s de estudio, y finalmente (e) como ocasional posavasos mientras se reflexiona profundamente acerca de co mo resolver los problemas de medida. Esperamos que a trave s de estos usos, sobre todo el u ltimo, aportar algu n conocimiento y ayuda que permita a los lectores aplicar adecuadamente las te cnicas y los conceptos abordados en este manual. The goal of the book is to provide readers with the tools necessary for assessing the psychometric qualities of educational and psychological measures as well as surveys and questionnaires. Each chapter will cover an issue pertinent to psychometric and measurement practice, with an emphasis on application. Topics will be briefly discussed from a theoretical/technical perspective in order to provide the reader with the background necessary to correctly use and interpret the statistical analyses that will be presented subsequently. The anticipated audience for this book includes researchers, practitioners, and graduate students searching for a guide to perform common psychometric analyses on various assessments, as discussed in many psychometric texts. We envision that this text will (a) patiently wait on some office shelves begging to be handed to a student as a resource, (b) have a permanent home on desks where it continually rises to the top of the stacks for daily use of the applied researcher, (c) be happily carried in bags to and from work and class by the graduate student learning techniques, (d) be listed proudly as a reference text on syllabi, and finally (e) as an occasional drink coaster while deep thoughts are pondered about how to solve measurement problems. We hope that through such uses, particularly the latter, that we have provided some insight and assistance to the user in appropriately applying the techniques and concepts discussed.

The book is designed primarily for graduate students (or advanced undergraduates) who are learning psychometrics, as well as professionals in the field who need a reference for use in their practice. We would assume that users have some basic knowledge of using SAS to read data and conduct basic analyses (e.g., descriptive statistics, frequency distributions). In addition, the reader should be familiar with basic statistical concepts such as descriptive statistics (e.g., mean, median, variance, standard deviation), percentiles and the rudiments of hypothesis testing. They should also have a passing familiarity with issues in psychometrics such as reliability, validity and test/survey scoring. The authors do not assume any more than basic familiarity with these issues, and devote a portion of each chapter (as well as the entire first chapter) to reviewing many of these basic ideas for those not familiar with them. This book will be useful either as a primary text for a course on applied measurement where SAS is the main platform for instruction, or as a supplement to a more theoretical text. The readership will include graduate students, faculty members, data analysts and psychometricians responsible for analysis of survey response data, as well as educational and psychological assessments. This book aims to provide readers with the tools necessary for assessing the psychometric qualities of educational and psychological measures as well as surveys and questionnaires. Each chapter covers an issue pertinent to psychometric and measurement practice, with an emphasis on application. Topics are briefly discussed from a theoretical/technical perspective in order to provide the reader with the background necessary to correctly use and interpret the statistical analyses that is presented subsequently. Readers are then presented with examples illustrating a particular concept (e.g., reliability). These examples include a discussion of the particular analysis, along with the SAS code necessary to conduct them. The resulting output is then discussed in detail, focusing on the interpretation of the results. Finally, examples of how these results might be written up is also included in the text. This mixture of theory with examples of actual practice will serve the reader both as a pedagogical tool and as a reference work.

The book is designed primarily for graduate students (or advanced undergraduates) who are learning psychometrics, as well as professionals in the field who need a reference for use in their practice. We would assume that users have some basic knowledge of using SAS to read data and conduct basic analyses (e.g., descriptive statistics, frequency distributions). In addition, the reader should be familiar with basic statistical concepts such as descriptive statistics (e.g., mean, median, variance, standard deviation), percentiles and the rudiments of hypothesis testing. They should also have a passing familiarity with issues in psychometrics such as reliability, validity and test/survey scoring. The authors do not assume any more than basic familiarity with these issues, and devote a portion of each chapter (as well as the entire first chapter) to reviewing many of these basic ideas for those not familiar with them. This book will be useful either as a primary text for a course on applied measurement where SAS is the main platform for instruction, or as a supplement to a more theoretical text. The readership will include graduate students, faculty members, data analysts and psychometricians responsible for analysis of survey response data, as well as educational and psychological assessments. This book aims to provide readers with the tools necessary for assessing the psychometric qualities of educational and psychological measures as well as surveys and questionnaires. Each chapter covers an issue pertinent to psychometric and measurement practice, with an emphasis on application. Topics are briefly discussed from a theoretical/technical perspective in order to provide the reader with the background necessary to correctly use and interpret the statistical analyses that is presented subsequently. Readers are then presented with examples illustrating a particular concept (e.g., reliability). These examples include a discussion of the particular analysis, along with the SAS code necessary to conduct them. The resulting output is then discussed in detail, focusing on the interpretation of the results. Finally, examples of how these results might be written up is also included in the text. This mixture of theory with examples of actual practice will serve the reader both as a pedagogical tool and as a reference work.

El objetivo del libro es proporcionar a los lectores las herramientas necesarias para evaluar la calidad psicome trica de las medidas educativas y psicolo gicas, asi como de encuestas y cuestionarios. Cada capi tulo aborda un tema relativo a la pra ctica psicome trica y de la medida, con e nfasis en la aplicacio n. Los temas sera n tratados brevemente desde una perspectiva teo rica/te cnica con el fin de proporcionar al lector los antecedentes necesarios para utilizar e interpretar correctamente los ana lisis estadi sticos que se presentara n con posteriormente. Este libro esta dirigido a investigadores, profesionales y estudiantes de posgrado (Ma ster y Doctorado) que buscan una gui a para realizar ana lisis psicome tricos de diferentes instrumentos de evaluacio n. Asumimos un nivel ba sico de conocimientos estadi sticos, pero estos conceptos se ira n repasando a lo largo de los diferentes capi tulos. Nos imaginamos que este texto (a) esperara pacientemente en algunos despachos implorando ser entregado, como recurso, a un estudiante, (b) tendra un lugar fijo en las mesas de los despachos donde continuamente, y debido a su uso diario, sera el primero del monto n, (c) estara en las mochilas de los estudiantes de postgrado, y los acompan ara felizmente desde casa al trabajo o a las clases y vuelta, (d) aparecera orgullosamente como un texto de referencia en los programas y guia s de estudio, y finalmente (e) como ocasional posavasos mientras se reflexiona profundamente acerca de co mo resolver los problemas de medida. Esperamos que a trave s de estos usos, sobre todo el u ltimo, aportar algu n conocimiento y ayuda que permita a los lectores aplicar adecuadamente las te cnicas y los conceptos abordados en este manual. The goal of the book is to provide readers with the tools necessary for assessing the psychometric qualities of educational and psychological measures as well as surveys and questionnaires. Each chapter will cover an issue pertinent to psychometric and measurement practice, with an emphasis on application. Topics will be briefly discussed from a theoretical/technical perspective in order to provide the reader with the background necessary to correctly use and interpret the statistical analyses that will be presented subsequently. The anticipated audience for this book includes researchers, practitioners, and graduate students searching for a guide to perform common psychometric analyses on various assessments, as discussed in many psychometric texts. We envision that this text will (a) patiently wait on some office shelves begging to be handed to a student as a resource, (b) have a permanent home on desks where it continually rises to the top of the stacks for daily use of the applied researcher, (c) be happily carried in bags to and from work and class by the graduate student learning techniques, (d) be listed proudly as a reference text on syllabi, and finally (e) as an occasional drink coaster while deep thoughts are pondered about how to solve measurement problems. We hope that through such uses, particularly the latter, that we have provided some insight and assistance to the user in appropriately applying the techniques and concepts discussed.