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Related Experiment Video

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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

A comparison of two estimation algorithms for Samejima's continuous IRT model.

Cengiz Zopluoglu¹

¹Department of Educational Psychology, University of Minnesota, 140 Education Sciences Building, 56 East River Road, Minneapolis, MN 55455-0364, USA. zoplu001@umn.edu

Behavior Research Methods

|June 27, 2012

Summary

A simplified expectation-maximization (EM) algorithm efficiently estimates parameters for Samejima's continuous response model (CRM). This psychometric approach shows potential for curriculum-based measurement (CBM) analysis in education.

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Area of Science:

Psychometrics
Educational Measurement
Computer Science

Background:

Samejima's continuous response model (CRM) is a psychometric tool.
Estimating item parameters for CRM is crucial for accurate analysis.
Curriculum-based measurement (CBM) in education requires robust analytical methods.

Purpose of the Study:

To compare the effectiveness and efficiency of two algorithms for estimating CRM item parameters.
To evaluate the applicability of CRM in the context of CBM.
To assess a simplified expectation-maximization (EM) algorithm against a traditional EM algorithm.

Main Methods:

Simulation study comparing two algorithms for CRM item parameter estimation.
Implementation of algorithms in computer software.
Real-data illustration using CRM for CBM outcomes.
Analysis of item parameter estimation accuracy and efficiency.

Main Results:

The simplified EM algorithm demonstrated comparable effectiveness and efficiency to the traditional EM algorithm for CRM item parameter estimation.
CRM shows promise as a psychometric tool for analyzing CBM data.
No significant differences were found between the two EM algorithms in this simulation.

Conclusions:

A simplified EM algorithm is a viable and efficient alternative for estimating CRM item parameters.
CRM holds potential for analyzing educational measurement outcomes in CBM.
Further research is recommended to establish CRM as a standard practice in CBM.