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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.
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