A Correlated Probit Model for Joint Modeling of Clustered Binary and Continuous Responses Author(s): Ralitza V. Gueorguieva and Alan Agresti Source: Journal of the American Statistical Association, Vol. 96, NoSep.

Source URL: www.stat.ufl.edu

A general formulation of the cross-nested logit model Michel Bierlaire, EPFL Conference paper STRC 2001 Session: Choices

Source URL: www.strc.ch

• Statistics
• Regression analysis
• Single-equation methods
• Statistical models
• Choice modelling
• Discrete choice
• Logit
• Mode choice
• Multinomial logistic regression
• Logistic regression
• Maximum likelihood estimation
• Probit

Published as "A Test of the Normality Assumption in the Ordered Probit Model," 1996, METRON, LIV:A Test of the Normality Assumption in the Ordered Probit Model‡ Paul A. Johnson

Source URL: irving.vassar.edu

• Latin script
• Probit
• Normal distribution
• Ñ
• Œ
• Anglo-Saxon runes
• N
• Statistical hypothesis testing
• Statistics
• Econometrics
• ISO 15924

A New Methodology for Modelling Stochastically the Time to Capsize Qi Chen, Andrzej Jasionowski, The Ship Stability Research Centre, Department of Naval Architecture and Mari

Source URL: floodstand.aalto.fi

• Statistical theory
• Statistical models
• Bayesian inference
• Capsizing
• Markov chain
• Normal distribution
• Generalized linear model
• Bayesian linear regression
• Probit
• Statistics
• Bayesian statistics
• Regression analysis

WHY DO MUNICIPALITIES RECYCLE: USING BAYESIAN PANEL SPATIAL AUTOREGRESSIVE PROBIT MODEL TAKEHRIO USUI; KAKAMU KAZUHIKO; MITSUKO CHIKASADA SOKA UNIVERSITY, JAPAN. Abstract:

Source URL: www.isecoeco.org

Large Deviations and Multinomial Probit Choice∗ Emin Dokumacı† and William H. Sandholm‡ July 4, 2011 Abstract We consider a discrete choice model in which the payoffs to each of an agent’s n actions are subjecte

Source URL: www.ssc.wisc.edu

0.1 chopit: Compound Hierarchical Ordered Probit for Survey Vignettes The Compound Hierarchical Ordered Probit (chopit) model corrects for “differential item

Source URL: perso.md2t.eu

0.1 bprobit: Bivariate Logistic Regression for Two Dichotomous Dependent Variables Use the bivariate probit regression model if you have two binaryrun dependent variables (Y1 , Y2 ), and wish to model them jointly as a

Source URL: perso.md2t.eu

0.1 oprobit: Ordinal Probit Regression for Ordered Categorical Dependent Variables Use the ordinal probit regression model if your dependent variables are ordered and categorical. They may take on either integer values

Source URL: perso.md2t.eu

0.1 probit.mixed: Mixed effects probit Regression Use generalized multi-level linear regression if you have covariates that are grouped according to one or more classification factors. The probit model is appropriate wh

Source URL: perso.md2t.eu

• Statistical models
• Estimation theory
• Analysis of variance
• Linear regression
• Fixed effects model
• Probit model
• Random effects model
• Linear model
• Normal distribution
• Statistics
• Regression analysis
• Econometrics