Substantive Theory and Constructive Measures
A Collection of Chapters and Measurement Commentary on Causal Science
Substantive Theory and Constructive Measures is a worthwhile and thorough investment for anyone in the research or data science fields.
A thorough and educational review, Mark Stone and Jack Stenner’s graduate level Substantive Theory and Constructive Measures will be a valuable resource for students and researchers in the sciences.
While graduate students could make use of this text as an overview of causal data measurement, it could also be a good resource for established professionals. The subject matter could not be more central to the proper collection and analysis of scientific data, and while the book is not a ready reference on this topic, its range is broad enough that it may function as a good starting point for research. Measurement and analysis pertaining to multiple disciplines—including temperature, star magnitude, and reading levels—appears in the text both through examples and in its study of methodology. Clear examples and the text’s willingness to explain basics make it much more accessible.
In addition to its potential educational uses, this work could function as a review for established professionals who are in the process of engineering a study. Its range of examples is not necessarily exhaustive for all disciplines involving causal data, but it is nevertheless broad enough to provide background and inspiration for the intrepid study author.
The book is no light read, but students familiar with data science should find it accessible and sometimes even enjoyable. The authors do their best to enhance their topic with concrete examples, visuals, and equations. While not typically artistic, the text gets its point across with good workmanship. Concepts are clear and well laid out, and if the book is slow going, this has much more to do with the density of its subject matter than the proficiency of its writers. Prior familiarity with the Rasch model for creating metrics, as well as some comfort with mathematical statistics methods, is strongly advised for full appreciation.
Much can be said about the amount of research and attention that went into Substantive Theory and Constructive Measures. Founded on the basics, its meticulous index and bibliography ensures that it will be a valuable addition to any curriculum or library.
Substantive Theory and Constructive Measures, while potentially too intellectually hefty for a newcomer to the field, is nevertheless likely to prove useful. It is a worthwhile investment for anyone in the research or data science fields.
Reviewed by
Anna Call
Disclosure: This article is not an endorsement, but a review. The publisher of this book provided free copies of the book and paid a small fee to have their book reviewed by a professional reviewer. Foreword Reviews and Clarion Reviews make no guarantee that the publisher will receive a positive review. Foreword Magazine, Inc. is disclosing this in accordance with the Federal Trade Commission’s 16 CFR, Part 255.
