A Generalized Model With Internal Restrictions on Item Difficulty for Polytomous Items
Bibliographic Data
| ID | 20283263 |
|---|---|
| Authors | Wen-Chung Wang (Education University of Hong Kong), Wen‐chung Wang (0000-0001-6022-1567, Education University of Hong Kong, corresponding author), Kuan‐Yu Jin (0000-0002-0327-7529, National Chung Cheng University), Kuan-Yu Jin (National Chung Cheng University, Chia-Yi, Taiwan) |
| Year | 2010 |
| Volume | 70 |
| Issue | 2 |
| Pages | 181-198 |
| Publication date | 2010-04-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Educational and Psychological Measurement (JOURNAL) |
| Journal identifiers | ISSN: 0013-1644 • E-ISSN: 1552-3888 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/0013164409344551 |
| OpenAlex | W2109777044 |
| Language | EN |
| Citations received | 3 |
| References cited | 24 |
In this study, the authors extend the standard item response model with internal restrictions on item difficulty (MIRID) to fit polytomous items using cumulative logits and adjacent-category logits. Moreover, the new model incorporates discrimination parameters and is rooted in a multilevel framework. It is a nonlinear mixed model so that existing parameter estimation procedures and computer packages for nonlinear mixed models can be directly adopted to estimate the parameters. Through simulations, it was found that the SAS NLMIXED procedure could recover the parameters fairly well and produce appropriate standard errors, except when the two-parameter adjacent-category logits MIRID was fit to data with a small sample size and a short test length; overall, cumulative logits yielded a better parameter recovery than adjacent-category logits. A real data set about guilt was analyzed with gender as a Level 2 predictor to illustrate applications and applications of the new model. Further model generalization is discussed
Generalization · Item response theory · Nonlinear system · Polytomous Rasch model · Psychometrics · Sample (material) · Set (abstract data type) · Statistics · Advanced Statistical Modeling Techniques · Computer Science · Mathematics · Psychometric Methodologies and Testing · Statistical Methods and Bayesian Inference
Generalized Latent Variable Modeling
Explanatory Item Response Models
A Rasch Model for Partial Credit Scoring
The linear logistic test model as an instrument in educational research
Scaling Performance Assessments
A Generalized Partial Credit Model
A Componential IRT Model for Guilt
The phenomenology of shame and guilt
| Unique citing works | 3 |
|---|---|
| Citations per year | 0,2 |
| Citation span | 2011 - 2020 (10) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 3 |