We review the theory of the latent Markov model for univariate and multivariate ordinal responses. They frequently occur when the data are related to social and medical surveys, and also in other fields of application where the order among the response categories can be made according to subject matter knowledge. We review how to assess the influence of covariates according to a chosen link function based on local, global, or continuation logits, or by an ordered probit link function. In this way, the model parameters can retain the ordinal structure imposed by the data. We show the statistical algorithms required for the parameters estimation and through examples based on real data we show how predictions can be achieved.

Pennoni, F. (2017). A review of panel data models with a Markov dependent structure for univariate and multivariate ordinal responses. In Book of Abstracts Cfe-Cmstatistics 2017 (pp.61-61).

A review of panel data models with a Markov dependent structure for univariate and multivariate ordinal responses

Pennoni, F.
Primo
2017

Abstract

We review the theory of the latent Markov model for univariate and multivariate ordinal responses. They frequently occur when the data are related to social and medical surveys, and also in other fields of application where the order among the response categories can be made according to subject matter knowledge. We review how to assess the influence of covariates according to a chosen link function based on local, global, or continuation logits, or by an ordered probit link function. In this way, the model parameters can retain the ordinal structure imposed by the data. We show the statistical algorithms required for the parameters estimation and through examples based on real data we show how predictions can be achieved.
abstract + slide
Expectation-Maximization algorithm, creditworthiness, missing data, Viterbi algorithm
English
11th International Conference on Computational and Financial Econometrics and 10th International conference of the ERCIM working group on Computatinal and Methodological Statistics
2017
Gonzalez-Rodriguez, G; Hofmann, M
Book of Abstracts Cfe-Cmstatistics 2017
9789963222742
dic-2017
2017
61
61
http://cmstatistics.org/CMStatistics2017/
none
Pennoni, F. (2017). A review of panel data models with a Markov dependent structure for univariate and multivariate ordinal responses. In Book of Abstracts Cfe-Cmstatistics 2017 (pp.61-61).
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/178057
Citazioni
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
Social impact