A marginalization model for the multidimensional unfolding analysis of ranking data
Bibliographic Data
| ID | 19277405 |
|---|---|
| Authors | HIROSHI HOJO (corresponding author) |
| Year | 1997 |
| Volume | 39 |
| Issue | 1 |
| Pages | 33-42 |
| Publication date | 1997-03-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Japanese Psychological Research (JOURNAL) |
| Journal identifiers | ISSN: 0021-5368 • E-ISSN: 1468-5884 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/1468-5884.00034 |
| OpenAlex | W1965257954 |
| Language | EN |
| Citations received | 2 |
| References cited | 2 |
A marginalization model for the multidimensional unfolding analysis of ranking data is presented. A subject samples one of a number of random points that are multivariate normally distributed. The subject perceives the distances from the point to all the stimulus points fixed in the same multidimensional space. The distances are error perturbed in this perception process. He/she produces a ranking dependent on these error‐perturbed distances. The marginal probability of a ranking is obtained according to this ranking model and by integrating out the subject (ideal point) parameters, assuming the above distribution. One advantage of the model is that the individual differences are captured using the posterior probabilities of subject points. Three sets of ranking data are analyzed by the model
Ideal point · Multivariate statistics · Point process · Ranking (information retrieval) · Statistics · Artificial Intelligence · Computer Science · Mathematics · Multi-Criteria Decision Making
| Citations per year | 0.07 |
|---|---|
| Citation span | 1998 - 2003 (6) |
| Highly cited | No |