Abstract
This study compares two algorithms, as implemented in two different computer softwares, that have appeared in the literature for estimating item parameters of Samejima's continuous response model (CRM) in a simulation environment. In addition to the simulation study, a real-data illustration is provided, and CRM is used as a potential psychometric tool for analyzing measurement outcomes in the context of curriculum-based measurement (CBM) in the field of education. The results indicate that a simplified expectation-maximization (EM) algorithm is as effective and efficient as the traditional EM algorithm for estimating the CRM item parameters. The results also show promise for using this psychometric model to analyze CBM outcomes, although more research is needed in order to recommend CRM as a standard practice in the CBM context.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 54-64 |
| Number of pages | 11 |
| Journal | Behavior Research Methods |
| Volume | 45 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 4 2013 |
| Externally published | Yes |
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Keywords
- Continuous IRT model
- Continuous response model
- Curriculum-based measurement
- Item parameter estimation
- Item parameter recovery
- Item response theory
- Simulation
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Psychology (miscellaneous)
- Psychology(all)
Cite this
A comparison of two estimation algorithms for Samejima's continuous IRT model. / Zopluoglu, Cengiz.
In: Behavior Research Methods, Vol. 45, No. 1, 04.03.2013, p. 54-64.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A comparison of two estimation algorithms for Samejima's continuous IRT model
AU - Zopluoglu, Cengiz
PY - 2013/3/4
Y1 - 2013/3/4
N2 - This study compares two algorithms, as implemented in two different computer softwares, that have appeared in the literature for estimating item parameters of Samejima's continuous response model (CRM) in a simulation environment. In addition to the simulation study, a real-data illustration is provided, and CRM is used as a potential psychometric tool for analyzing measurement outcomes in the context of curriculum-based measurement (CBM) in the field of education. The results indicate that a simplified expectation-maximization (EM) algorithm is as effective and efficient as the traditional EM algorithm for estimating the CRM item parameters. The results also show promise for using this psychometric model to analyze CBM outcomes, although more research is needed in order to recommend CRM as a standard practice in the CBM context.
AB - This study compares two algorithms, as implemented in two different computer softwares, that have appeared in the literature for estimating item parameters of Samejima's continuous response model (CRM) in a simulation environment. In addition to the simulation study, a real-data illustration is provided, and CRM is used as a potential psychometric tool for analyzing measurement outcomes in the context of curriculum-based measurement (CBM) in the field of education. The results indicate that a simplified expectation-maximization (EM) algorithm is as effective and efficient as the traditional EM algorithm for estimating the CRM item parameters. The results also show promise for using this psychometric model to analyze CBM outcomes, although more research is needed in order to recommend CRM as a standard practice in the CBM context.
KW - Continuous IRT model
KW - Continuous response model
KW - Curriculum-based measurement
KW - Item parameter estimation
KW - Item parameter recovery
KW - Item response theory
KW - Simulation
UR - http://www.scopus.com/inward/record.url?scp=84874355623&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874355623&partnerID=8YFLogxK
U2 - 10.3758/s13428-012-0229-6
DO - 10.3758/s13428-012-0229-6
M3 - Article
C2 - 22733227
AN - SCOPUS:84874355623
VL - 45
SP - 54
EP - 64
JO - Behavior Research Methods
JF - Behavior Research Methods
SN - 1554-351X
IS - 1
ER -