Causal Rasch Models
Frontiers in Psychology: Quantitative Psychology and Measurement, 4(536), 1-14 [doi: 10.3389/fpsyg.2013.00536].
14 Pages Posted: 20 Oct 2013
Date Written: August 23, 2013
Abstract
Rasch’s unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader-text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained.
Keywords: Rasch models, causality, prediction, measurement, reading theory, quantification, educational assessment
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