Introduction to Psychometric Theory

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A01=George A. Marcoulides
A01=Tenko Raykov
advanced latent variable modeling applications
Age Group_Uncategorized
Age Group_Uncategorized
Author_George A. Marcoulides
Author_Tenko Raykov
automatic-update
Category1=Non-Fiction
Category=JMA
Category=JMBT
Category=JNKD
Category=JNT
Category=MMJT
classical
Composite Reliability
COP=United Kingdom
Criterion Validity Coefficient
Data Set
Delivery_Delivery within 10-20 working days
Difficulty Parameter
educational assessment techniques
eq_bestseller
eq_isMigrated=0
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Error Score
Fa Model
Interval Estimation
IRT
IRT Model
item
item response modeling
Language_English
latent
Latent Constructs
measurement error analysis
Measuring Instrument
Model Fit
Model Result
modeling
mplus
Mplus Input File
Normal Ogive
Observed Score
PA=Available
Price_€100 and above
Probability RMSEA
Propensity Distributions
PS=Active
psychometric reliability
Psychometric Theory
Reliability Index
response
score
Single Factor Model
social science statistics
softlaunch
test
Traditional Fa Model
true
True Score
True Score Equivalent
validity assessment methods
variable
WAIS Subtest

Product details

  • ISBN 9780415878227
  • Weight: 818g
  • Dimensions: 178 x 254mm
  • Publication Date: 22 Sep 2010
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
  • Language: English
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This new text provides a state-of the-art introduction to educational and psychological testing and measurement theory that reflects many intellectual developments of the past two decades. The book introduces psychometric theory using a latent variable modeling (LVM) framework and emphasizes interval estimation throughout, so as to better prepare readers for studying more advanced topics later in their careers. Featuring numerous examples, it presents an applied approach to conducting testing and measurement in the behavioral, social, and educational sciences. Readers will find numerous tips on how to use test theory in today’s actual testing situations.

To reflect the growing use of statistical software in psychometrics, the authors introduce the use of Mplus after the first few chapters. IBM SPSS, SAS, and R are also featured in several chapters. Software codes and associated outputs are reviewed throughout to enhance comprehension. Essentially all of the data used in the book are available on the website. In addition instructors will find helpful PowerPoint lecture slides and questions and problems for each chapter.

The authors rely on LVM when discussing fundamental concepts such as exploratory and confirmatory factor analysis, test theory, generalizability theory, reliability and validity, interval estimation, nonlinear factor analysis, generalized linear modeling, and item response theory. The varied applications make this book a valuable tool for those in the behavioral, social, educational, and biomedical disciplines, as well as in business, economics, and marketing. A brief introduction to R is also provided.

Intended as a text for advanced undergraduate and/or graduate courses in psychometrics, testing and measurement, measurement theory, psychological testing, and/or educational and/or psychological measurement taught in departments of psychology, education, human development, epidemiology, business, and marketing, it will also appeal to researchers in these disciplines. Prerequisites include an introduction to statistics with exposure to regression analysis and ANOVA. Familiarity with SPSS, SAS, STATA, or R is also beneficial. As a whole, the book provides an invaluable introduction to measurement and test theory to those with limited or no familiarity with the mathematical and statistical procedures involved in measurement and testing.

Tenko Raykov is Professor of Measurement and Quantitative Methods at Michigan State University. He received his Ph.D. in Mathematical Psychology from Humboldt University in Berlin. He teaches courses in psychometric theory, multivariate statistics, latent variable and structural equation modeling, and multilevel modeling at Michigan State University. He serves on the editorial board of Psychological Methods, Structural Equation Modeling, the British Journal of Mathematical and Statistical Psychology, and Multivariate Behavioral Research. George A. Marcoulides is Professor of Statistics at the University of California – Riverside. He is the Series Editor of the Quantitative Methodology Series, Editor of the Structural Equation Modeling journal, and on the editorial board of several other measurement and statistics journals.

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