What is a "correct" measure in the presence of disturbing influences (biases)? The answer depends on the goal of the researcher. If the goal is to create reproducible measures, measures which are the same from one testing situation to another, the "correct" measure is the unbiased one - so long as all measures are subject to the same iterative process of removing biases and misfits. If the goal is to describe the outcome of a particular testing situation, the biased measure is more reflective of what actually happened.
This was crucial during a recent analysis of data compression methods for audio samples. In the Figure below, the "biased" measure for each data compression "Codec" is the measure produced by the complete data. The "unbiased" measure is produced by omitting idiosyncratic portions of the data. Notice that the measure for Codec 4 changes substantially relative to the others depending on whether biased data are included. Which is the "correct" measure of Codec 4?
Approximately 75% of the drop in Codec 4 is due to an interaction with one audio sample featuring percussion. It performed consistently on the other samples. This identified for removal a technical error that caused the percussion interaction. Thus, even though the observed data produce the "biased" measure, the "correct" measure for future development is the "unbiased" one!
Biased or unbiased measures.Moulton M. Rasch Measurement Transactions, 1998, 12:3 p. 649.
|Rasch Measurement Transactions (free, online)||Rasch Measurement research papers (free, online)||Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch||Applying the Rasch Model 3rd. Ed., Bond & Fox||Best Test Design, Wright & Stone|
|Rating Scale Analysis, Wright & Masters||Introduction to Rasch Measurement, E. Smith & R. Smith||Introduction to Many-Facet Rasch Measurement, Thomas Eckes||Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr.||Statistical Analyses for Language Testers, Rita Green|
|Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar||Journal of Applied Measurement||Rasch models for measurement, David Andrich||Constructing Measures, Mark Wilson||Rasch Analysis in the Human Sciences, Boone, Stave, Yale|
|in Spanish:||Análisis de Rasch para todos, Agustín Tristán||Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez|
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