Substantive Theory and Constructive Measures

A Collection of Chapters and Measurement Commentary on Causal Science

by Mark Stone & Jack Stenner


Formats

Hardcover
$31.99
Softcover
$20.99
E-Book
$4.99
Hardcover
$31.99

Book Details

Language : English
Publication Date : 5/15/2018

Recognition Programs


Format : Hardcover
Dimensions : 6x9
Page Count : 372
ISBN : 9781532036538
Format : Softcover
Dimensions : 6x9
Page Count : 372
ISBN : 9781532036514
Format : E-Book
Dimensions : N/A
Page Count : 372
ISBN : 9781532036521

About the Book

Stone and Stenner propose Substantive-Theory and Constructive Measures as crucial elements in determining predictive measures and variance to advance causation in a specified frame of reference. The collected chapters and supplementary measurement commentary provide the details to this approach. Redundancy is purposeful in demonstrating the primacy of theory over data. The collective process is contained in the measurement mechanism, which embodies substantive theory, constructed instrumentation, and assembled data supporting spot-on prediction or identifying error—causal science.


About the Author

Jack Stenner and Mark Stone have been collaborating for more than forty years on issues of measurement and reading theory. Dr. Stone is a licensed clinical psychologist, board certified in school psychology and clinical psychology (ABPP). A MESA graduate, he retired as vice president and academic dean of the Adler Institute, where he taught research design and statistics. He now teaches at Aurora University and supervises doctoral dissertations. Dr. Stenner is chief science officer and cofounder of MetaMetrics Inc. He is research professor in the Applied Developmental Sciences and Special Education program, School of Education, at the University of North Carolina at Chapel Hill and chief science officer at MetaMetrics—developers of the Lexile Framework for Reading and the Quantile Framework for Mathematics. Dr. Donald Burdick, PhD, coauthored with Jack and Mark How to Model and Test for Mechanisms That Make Measurement Systems Work.