Assessment of Differential Rater Functioning in Latent Classes with New Mixture Facets Models
Bibliographic Data
| ID | 19291306 |
|---|---|
| Authors | Kuan‐Yu Jin (0000-0002-0327-7529, Education University of Hong Kong, corresponding author), Kuan-Yu Jin (Department of Psychology, The Education University of Hong Kong), Wen-Chung Wang (Department of Psychology, The Education University of Hong Kong), Wen‐chung Wang (0000-0001-6022-1567, Education University of Hong Kong) |
| Year | 2017 |
| Volume | 52 |
| Issue | 3 |
| Pages | 391-402 |
| Publication date | 2017-05-04 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Multivariate Behavioral Research (JOURNAL) |
| Journal identifiers | ISSN: 0027-3171 • E-ISSN: 1532-7906 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00273171.2017.1299615 |
| PMID | 28328280 |
| OpenAlex | W2597798565 |
| Language | EN |
| Citations received | 4 |
| References cited | 37 |
Multifaceted data are very common in the human sciences. For example, test takers' responses to essay items are marked by raters. If multifaceted data are analyzed with standard facets models, it is assumed there is no interaction between facets. In reality, an interaction between facets can occur, referred to as differential facet functioning. A special case of differential facet functioning is the interaction between ratees and raters, referred to as differential rater functioning (DRF). In existing DRF studies, the group membership of ratees is known, such as gender or ethnicity. However, DRF may occur when the group membership is unknown (latent) and thus has to be estimated from data. To solve this problem, in this study, we developed a new mixture facets model to assess DRF when the group membership is latent and we provided two empirical examples to demonstrate its applications. A series of simulations were also conducted to evaluate the performance of the new model in the DRF assessment in the Bayesian framework. Results supported the use of the mixture facets model because all parameters were recovered fairly well, and the more data there were, the better the parameter recovery
Bayesian probability · Cognitive psychology · Developmental psychology · Differential (mechanical device) · Differential item functioning · Econometrics · Facet (psychology) · Item response theory · Mixture model · Psychometrics · Statistics · Advanced Statistical Methods and Models · Artificial Intelligence · Computer Science · Mathematics · Psychology · Psychometric Methodologies and Testing · Social Psychology · Statistical Methods and Bayesian Inference
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Formulation and Application of the Generalized Multilevel Facets Model
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Rater bias patterns in an EFL writing assessment
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Saltus
| Unique citing works | 4 |
|---|---|
| Citations per year | 0,57 |
| Citation span | 2019 - 2023 (5) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 4 |