Results 251 to 260 of about 43,267 (279)

On the Multivariate Probit Model for Exchangeable Binary Data with Covariates

Biometrical Journal, 2005
This paper considers the use of a multivariate binomial probit model for the analysis of correlated exchangeable binary data. The model can naturally accommodate both cluster and individual level covariates, while keeping a fairly flexible intracluster association structure.
Catalina, Stefanescu, Bruce W, Turnbull
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Bayesian inference in the multivariate probit model

2007
Correlated binary data arise in many applications. Any analysis of this type of data should take into account the correlation structure among the variables. The multivariate Probit model (MVP), introduced by Ashford and Snowden (1970), is a popular class of models particularly suitable for the analysis of correlated binary data.
openaire   +1 more source

A limited information estimator for the multivariate ordinal probit model

Applied Economics, 2000
A limited information estimator for the multivariate ordinal probit model is developed. The main advantage of the estimator is that even for high dimensional models, the estimation procedure requires the evaluation of bivariate normal integrals only. The proposed estimator also avoids the potential problem of encountering local maxima in the estimation
Fu, Tsu-Tan, Li, Lung-An, Lin, Yih-Ming, Kan, Kamhon   +3 more
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A probit model for multivariate random length ordinal data

Communications in Statistics - Theory and Methods, 1998
Multivariate random length ordinal data are data such that the ordinal response variable is observed a random number of times for each experimen¬tal unit. For example, depression may occur a random number of times and the severity of each depression episode is measured by an ordinal scale (e.g., l=mildly depressed, 2=moderately depressed, 3=very ...
openaire   +1 more source

Composite Likelihood Estimation for Multivariate Probit Latent Traits Models

Communications in Statistics - Theory and Methods, 2013
Inference in generalized linear mixed models with multivariate random effects is often made cumbersome by the high-dimensional intractable integrals involved in the marginal likelihood. This article presents an inferential methodology based on the marginal composite likelihood approach for the probit latent traits models.
openaire   +1 more source

Estimation of multivariate probit models by exact maximum likelihood [PDF]

, 2009
In this paper, we develop a new numerical method to estimate a multivariate probit model. To this end, we derive a new decomposition of normal multivariate integrals that has two appealing properties. First, the decomposition may be written as the sum of normal multivariate integrals, in which the highest dimension of the integrands is reduced relative
Jacques Huguenin, Florian Pelgrin, Alberto Holly   +2 more
openaire  

Analysis of Purchasing Decision with Multivariate Probit

American Journal of Agricultural Economics, 1971
Paul Kau, Lowell Hill
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Addressing unobserved heterogeneity in the analysis of bicycle crash injuries in Scotland: A correlated random parameters ordered probit approach with heterogeneity in means

Analytic Methods in Accident Research, 2021
Grigorios Fountas, Achille Fonzone, Adebola Olowosegun   +2 more
exaly  

The use of logit and probit models in strategic management research: Critical issues

Strategic Management Journal, 2007
Glenn Hoetker
exaly  

The persistence of energy poverty: A dynamic probit analysis

Energy Economics, 2020
Yonas Alem
exaly