Results 251 to 260 of about 331,548 (294)

Morphoscopic ancestry estimates in Filipino crania using multivariate probit regression models

American Journal of Physical Anthropology, 2020
AbstractObjectivesProbit has not been applied to ancestry estimation in forensic anthropology. The goals of this study were to: (1) evaluate the performance of probit analysis as a classification tool for ancestry estimation using ordinal data and (2) expand our current understanding of human cranial variation for an understudied population ...
Matthew C. Go, Joseph T. Hefner
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The recursive impact in the multivariate probit model: An application on farmers’ decisions for opting risk management strategies

Agricultural Economics
This study investigates the determinants of farmers’ risk management decisions in Khyber‐Pakhtunkhwa, Pakistan, using a recursive multivariate probit (RMVP) model. Employing data from 382 farmers collected through a multistage sampling process, the study
Jamal Shah, Majed Alharthi
semanticscholar   +1 more source

Multivariate probit linear mixed models for multivariate longitudinal binary data

Statistics in Medicine
When analyzing multivariate longitudinal binary data, we estimate the effects on the responses of the covariates while accounting for three types of complex correlations present in the data. These include the correlations within separate responses over time, cross‐correlations between different responses at different times, and correlations between ...
Kuo‐Jung Lee, Chanmin Kim, Jae Keun Yoo, Keunbaik Lee   +3 more
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Bayesian Analysis of Multivariate Probit Models [PDF]

, 1996
This paper provides a unified simulation-based Bayesian and non-Bayesian analysis of correlated binary data using the multivariate probit model. The posterior distribution is simulated by Markov chain Monte Carlo methods, and maximum likelihood estimates are obtained by a Markov chain Monte Carlo version of the E-M algorithm.
Siddhartha Chib, Edward Greenberg
openaire  

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 ...
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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.
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How do the Determinants of Electric Vehicle Adoption Change Over Time? A Multivariate Ordered Probit Analysis

2024 Forum for Innovative Sustainable Transportation Systems (FISTS)
The existing literature on electric vehicles (EVs) lacks a time-based differentiation in adoption patterns. This paper examines the evolving factors influencing EV adoption over time via a stated preference survey. The sample includes 718 adult residents
Bruno Cesar Krause Moras, Prasanna Humagain, Konstantina Gkritza   +2 more
semanticscholar   +1 more source

Bayesian analysis of multivariate ordered probit model with individual heterogeneity

AStA Advances in Statistical Analysis, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Parameter‐expandeddata augmentation for analyzing correlated binary data using multivariate probit models

Statistics in Medicine, 2020
Data augmentation has been commonly utilized to analyze correlated binary data using multivariate probit models in Bayesian analysis. However, the identification issue in the multivariate probit models necessitates a rigorous Metropolis‐Hastings algorithm for sampling a correlation matrix, which may cause slow convergence and inefficiency of Markov ...
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Maximum likelihood estimation of multinomial probit factor analysis models for multivariate t-distribution

Computational Statistics, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jiang, Jie, Liu, Xinsheng, Yu, Keming
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