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Psychometric theory
752 pages
A comprehensive, authoritative dive into the mechanics of measurement and statistical inference.
What it feels like
Reading this classic text feels like stepping into a rigorous, well-structured graduate seminar. The pace is steady and deliberate, guiding the reader through the intricate landscape of measurement problems with an authoritative, instructional tone. It cultivates a focused, scholarly mood, demanding intellectual engagement while remaining accessible to those with a basic background in statistics. The prose is analytical and comprehensive, meticulously bridging classical procedures of variance with modern inferential techniques. It is an experience defined by clarity and academic rigor, offering a deep, foundational understanding of psychological testing and research methodology. This book will deeply satisfy graduate students and researchers in psychology, education, and business who are looking to master the theoretical underpinnings of psychometrics.
- Mood
- intellectual
- focused
- scholarly
- Tone
- academic
- authoritative
- instructional
- analytical
- Pace
- steady
- Themes
- measurement theory · statistical analysis · psychological testing · research methodology
- The writing
- Clear, comprehensive, and structured, designed to bridge classical variance procedures with modern inferential statistics.
- The arc
- A journey from foundational statistical concepts to a comprehensive understanding of complex measurement problems.
- Who it's for
- Graduate students and researchers in psychology, education, and business who need a thorough grounding in measurement and psychometrics.
About the book
(Publisher-supplied data) The classic text is Psychometric Theory. Like the previous edition, this text is designed as a comprehensive text in measurement for researchers and for use in graduate courses in psychology, education and areas of business such as management and marketing. It is intended to consider the broad measurement problems that arise in these areas and is written for a reader who needs only a basic background in statistics to comprehend the material. It also combines classical procedures that explain variance with modern inferential procedures.
Description from Open Library.
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