What We Measure Matters

This comment was posted in reply to Chris Conley’s recent blog athttp://www.huffingtonpost.com/chip-conley/what-we-measure-matters_b_204676.html.

Right on, Chip!

The focus on meaning is essential. And unbeknownst to just about everyone but geeks like me, there is an extensive, longstanding, and mathematically rigorous scientific literature on meaningfulness in measurement.

We need to follow through from meaningful content to meaningful numbers, since survey and assessment ratings, scores, and response percentages are NOT measures in the everyday sense of what we mean when we deal with weight scales, clocks, thermometers, or rulers. That is, these numbers do not and cannot stand for something that adds up in the same way they do. The meaning of any given unit difference changes depending on where it falls in the measurement range, on who is measured, and/or on which item(s) are measuring.

For something we want to measure to be mapped onto a number line and to be truly and fully quantified, data have to have certain properties, like additivity, sufficiency, invariance, separable parameters, etc. When those properties are obtained, an instrument can be calibrated, data volume dramatically reduced, data quality assessed in terms of its internal consistency, and the measures made meaningfully interpretable.

Fortunately, scientific scaling methods have been applied in high stakes graduation, admissions, and professional certification/licensure testing for almost 40 years. Over the last 30 years, they have come to be applied in all kinds of survey research in health care and management consulting. Contact me for more information, see my web site at www.livingcapitalmetrics.com, or see www.rasch.org for full text articles.
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