IRIS - Res&Arch Institutional Research Information System - Research & Archive
Anagrafe della Ricerca dell'Università degli Studi di Perugia.
EnglishTo analyze multiple categorical ordinal responses, a pseudo-Bayes approach is proposed which uses estimating equations based on the Constrained Fixed Point methodology. A set of ordinal scales, over social domains, are considered intrinsically related through latent mechanism of scaling which depends on individual choice process. Thus, a complex model is demanded, which is recursively structured over scale levels crossing social domains. Since usual approaches are difficult to implement, we use a non standard pseudo-Bayes approach (the Con-strained Fixed Point) which shares basic ideas with the Prior Feedback Setup (Casella & Robert, 2002). It provides a power tool which may be complementary to standard approaches. It is sufficiently general and flexible, conceptually simple and statistically grounded. Operatively, it is easy to implement and computationally efficient, at least for large families of models.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
| Titolo: | A Residual From Updating Based Approach for Multiple Categorical Ordinal Responses | |
| Autori: | ||
| Data di pubblicazione: | 2006 | |
| Abstract: | To analyze multiple categorical ordinal responses, a pseudo-Bayes approach is proposed which uses... estimating equations based on the Constrained Fixed Point methodology. A set of ordinal scales, over social domains, are considered intrinsically related through latent mechanism of scaling which depends on individual choice process. Thus, a complex model is demanded, which is recursively structured over scale levels crossing social domains. Since usual approaches are difficult to implement, we use a non standard pseudo-Bayes approach (the Con-strained Fixed Point) which shares basic ideas with the Prior Feedback Setup (Casella & Robert, 2002). It provides a power tool which may be complementary to standard approaches. It is sufficiently general and flexible, conceptually simple and statistically grounded. Operatively, it is easy to implement and computationally efficient, at least for large families of models. | |
| Handle: | http://hdl.handle.net/11391/33570 | |
| ISBN: | 9783790817089 | |
| Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
File in questo prodotto:
Copyright © 2021