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Multivariate probit analysis: A neglected procedure in medical statistics
Statistics in Medicine, 1991AbstractThe multivariate probit model is designed to regress a vector of correlated quantal variables on a mixture of continuous and discrete predictors. Various applications can be found in the biological, economical and psychosociological literature, but the method is not yet widely used in medical applications.
E, Lesaffre, G, Molenberghs
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Emergence of childhood psychiatric disorders: a multivariate probit analysis
Statistics in Medicine, 1998We applied a computationally practical form of probit analysis for multiple response variables to data on early childhood development of four psychiatric disorders: disruptive disorders (DD-attention deficit disorders, oppositional defiant disorder, conduct disorder); adjustment disorders (ADJ); emotional disorders (ED-all anxiety disorders, depression)
R D, Gibbons, J V, Lavigne
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Testing for Dependence in Multivariate Probit Models
Biometrika, 1982SUMMARY A multivariate probit model is considered and the Lagrange multiplier or score statistic for testing independence is derived. The limiting distribution of the statistic takes a simple form under the null hypothesis and for local alternatives. The statistic is a natural generalization of Pearson's chi-squared for a 2 x 2 table.
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Multivariate probit linear mixed models for multivariate longitudinal binary data
Statistics in MedicineWhen 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 +3 more
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Identification in multivariate partial observability probit
International Journal of Mathematical Modelling and Numerical Optimisation, 2014Poirier (1980) considered a bivariate probit model in which the binary dependent variables y1 and y2 of a bivariate probit model were not observed individually, but the product z = y1 × y2 was observed. This paper expands this notion of partial observability to multivariate settings.
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1998
Probit analysis is used in the environmental toxicology field as a procedure to study the dosage response relation in a population of biological organisms, where randomly chosen population members are exposed to various levels of applied stimulus and quantal response is assessed as either dead or alive.
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Probit analysis is used in the environmental toxicology field as a procedure to study the dosage response relation in a population of biological organisms, where randomly chosen population members are exposed to various levels of applied stimulus and quantal response is assessed as either dead or alive.
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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
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Bayesian Analysis of Multivariate Probit Models with Surrogate Outcome Data
Psychometrika, 2010A new class of parametric models that generalize the multivariate probit model and the errors-in-variables model is developed to model and analyze ordinal data. A general model structure is assumed to accommodate the information that is obtained via surrogate variables. A hybrid Gibbs sampler is developed to estimate the model parameters.
Poon, Wai-Yin, Wang, Hai-Bin
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Morphoscopic ancestry estimates in Filipino crania using multivariate probit regression models
American Journal of Physical Anthropology, 2020AbstractObjectivesProbit 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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Traveler perceptions and airline choice: A multivariate probit approach
Journal of Air Transport Management, 2015Abstract We investigate the factors that affect passenger decisions regarding airline choice. Three Multivariate Probit (MP) models are developed to analyze data for a sample of 853 respondents. This methodology allows for modeling the simultaneous, yet separate, consideration of airline choice determinants. Fare, safety and reliability, and friendly-
Christina P. Milioti +2 more
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