ERIC Number: EJ1048603
Record Type: Journal
Publication Date: 2015-Feb
Abstractor: As Provided
Reference Count: 38
Maximum Likelihood Item Easiness Models for Test Theory without an Answer Key
France, Stephen L.; Batchelder, William H.
Educational and Psychological Measurement, v75 n1 p57-77 Feb 2015
Cultural consensus theory (CCT) is a data aggregation technique with many applications in the social and behavioral sciences. We describe the intuition and theory behind a set of CCT models for continuous type data using maximum likelihood inference methodology. We describe how bias parameters can be incorporated into these models. We introduce two extensions to the basic model in order to account for item rating easiness/difficulty. The first extension is a multiplicative model and the second is an additive model. We show how the multiplicative model is related to the Rasch model. We describe several maximum-likelihood estimation procedures for the models and discuss issues of model fit and identifiability. We describe how the CCT models could be used to give alternative consensus-based measures of reliability. We demonstrate the utility of both the basic and extended models on a set of essay rating data and give ideas for future research.
Descriptors: Maximum Likelihood Statistics, Test Items, Difficulty Level, Test Theory, Answer Keys, Statistical Inference, Models, Reliability, Scaling, Goodness of Fit, Essay Tests, Scoring
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Sponsor: Oak Ridge Institute for Science and Education (ORISE); Army Research Office (ARO)
Authoring Institution: N/A