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Introduction to Psychometric Theory
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.
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.
- GenresPsychology
352 pages, ebook
First published September 20, 2010
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24 people want to read
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Displaying 1 of 1 review
December 20, 2018
This book has some basic information, but it is extremely poorly written.
Throughout the book they put in parentheses different terms for the same thing. This would be great at the start —to learn all the various names people call something— but they keep doing it, and that breaks up the reading and adds tremendous cognitive load.
For example, in the intro sections, they talk about how the same thing might be called a test, a measure, and instrument, a scale, etc. Likewise, they talk about how these have items, which are also called components. That's great in the intro, but then they should have picked one word and stuck with it for their book. Instead, even in the last chapter, you get this sort of thing:
"More formally, a measuring instrument (test) is referred to as unidimentional if (a) its items (components) are ..."
"...valid notion of dimensionality of a behaviour measuring instrument (test, scale) ..."
"Specifically, if for a given test (set of items) ..."
These three examples are all in the same paragraph. And they keep doing this. It makes it very cumbersome to read, as as you can imagine, bloats the pages. If they had picked one word for their book and had a glossary of synonyms, it would have been a much shorter, easier to read book.
They also structure the book someone non-sensically. They just start talking about fine-grained details at the start of a chapter without telling you why, or how these details apply to the broader question, or what use they will be, or what they are trying to model with these details.
Very badly written book. Fine information, but not clear at all. Would not recommend, and would suggest that there are much clearer ways to learn this stuff.
Throughout the book they put in parentheses different terms for the same thing. This would be great at the start —to learn all the various names people call something— but they keep doing it, and that breaks up the reading and adds tremendous cognitive load.
For example, in the intro sections, they talk about how the same thing might be called a test, a measure, and instrument, a scale, etc. Likewise, they talk about how these have items, which are also called components. That's great in the intro, but then they should have picked one word and stuck with it for their book. Instead, even in the last chapter, you get this sort of thing:
"More formally, a measuring instrument (test) is referred to as unidimentional if (a) its items (components) are ..."
"...valid notion of dimensionality of a behaviour measuring instrument (test, scale) ..."
"Specifically, if for a given test (set of items) ..."
These three examples are all in the same paragraph. And they keep doing this. It makes it very cumbersome to read, as as you can imagine, bloats the pages. If they had picked one word for their book and had a glossary of synonyms, it would have been a much shorter, easier to read book.
They also structure the book someone non-sensically. They just start talking about fine-grained details at the start of a chapter without telling you why, or how these details apply to the broader question, or what use they will be, or what they are trying to model with these details.
Very badly written book. Fine information, but not clear at all. Would not recommend, and would suggest that there are much clearer ways to learn this stuff.
Displaying 1 of 1 review