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Multiple Choice Tests: Inferences Based on Estimators of Maximum Likelihood

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DOI: 10.4236/ojs.2014.46045    2,807 Downloads   3,781 Views  

ABSTRACT

This paper revises and expands the model Delta for estimating the knowledge level in multiple choice tests (MCT). This model was originally proposed by Martín and Luna in 1989 (British Journal of Mathematical and Statistical Psychology, 42: 251) considering conditional inference. Consequently, the aim of this paper is to obtain the unconditioned estimators by means of the maximum likelihood method. Besides considering some properties arising from the unconditional inference, some additional issues regarding this model are also going to be addressed, e.g. test-inversion confidence intervals and how to treat omitted answers. A free program that allows the calculations described in the document is available on the website http://www.ugr.es/local/bioest/Delta

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Femia-Marzo, P. and Martín-Andrés, A. (2014) Multiple Choice Tests: Inferences Based on Estimators of Maximum Likelihood. Open Journal of Statistics, 4, 466-483. doi: 10.4236/ojs.2014.46045.

References

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