Dear Talking Measurement colleagues,
I want to call your attention to two complementary articles that have just appeared in press this week in the Journal of Educational Measurement and Psychometrika. The abstracts for each article are appended below and I would be happy to send the full manuscripts to anyone that does not have online access to these journals. Both articles were motivated by the critiques of Joel Michell and others who are active members of this listserv that mainstream pychometrics represents a pathological science because it either ignores or intentionally obscures the assumption that latent variables are measurable in a classical sense of the word. Although neither article represents a revolutionary breakthrough, the fact that they have been published in (arguably) the two most mainstream outlets in psychometrics, seems significant. I hope that at a minimum the publication of these articles will establish a precedent in these mainstream outlets that will make it easier for others to publish subsequent essays and empirical analyses that help push the field of psychometrics forward in a productive, constructive and scientific manner.
Best wishes,
Derek
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Measuring Growth with Vertical Scales
Derek Briggs
Journal of Educational Measurement
Abstract
A vertical score scale is needed to measure growth across multiple tests
in terms of absolute changes in magnitude. Since the warrant for
subsequent growth interpretations depends upon the assumption that the
scale has interval properties, the validation of a vertical scale would
seem to require methods for distinguishing interval scales from ordinal
scales. In taking up this issue, two different perspectives on
educational measurement are contrasted: a metaphorical perspective and a
classical perspective. Although the metaphorical perspective is more
predominant, at present it provides no objective methods whereby the
properties of a vertical scale can be validated. In contrast, when
taking a classical perspective, the axioms of additive conjoint
measurement can be used to test the hypothesis that the latent variable
underlying a vertical scale is quantitative (supporting ratio or
interval properties) rather than merely qualitative (supporting ordinal
or nominal properties). The application of such an approach is
illustrated with both a hypothetical example and by drawing upon recent
research that has been conducted on the Lexile scale for reading
comprehension.
Evaluating the Equal-Interval Hypothesis with Test Score Scales Abstract
Ben Domingue
Psychometrika
Abstract
The axioms of additive conjoint measurement provide a means of testing the hypothesis that testing data can be placed onto a scale with equal-interval properties. However, the axioms are difficult to verify given that item responses may be subject to measurement error. A Bayesian method exists for imposing order restrictions from additive conjoint measurement while estimating the probability of a correct response. In this study an improved version of that methodology is evaluated via simulation. The approach is then applied to data from a reading assessment intentionally designed to support an equal-interval scaling.
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Derek Briggs
Professor & Program Chair
Research and Evaluation Methodology
Editor, Educational Measurement: Issues & Practice
School of Education, 249 UCBUniversity of Colorado
Boulder, CO 80309