A sensitivity analysis of two multivariate response models
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Publication:1361513
DOI10.1016/0167-9473(94)90018-3zbMath0937.62646OpenAlexW2074818082MaRDI QIDQ1361513
Emmanuel Lesaffre, Geert Molenberghs, Geert Verbeke
Publication date: 25 August 1997
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0167-9473(94)90018-3
associationodds ratiogeneralized linear modelsordinal variablesmultivariate Dale modeltetrachoric correlationmultivariate probit modelpolychoric correlation
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Modeling Clustered Ordered Categorical Data: A Survey ⋮ Prediction and classification when the diagnostic classes are related ⋮ Models for the association between ordinal variables. ⋮ Maximum Likelihood Estimation of Bivariate Logistic Models for Incomplete Responses with Indicators of Ignorable and Non-Ignorable Missingness
Uses Software
Cites Work
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- Longitudinal data analysis using generalized linear models
- Maximum likelihood estimation of the polychoric correlation coefficient
- Computing in statistical science through APL
- Models for Longitudinal Data: A Generalized Estimating Equation Approach
- Algorithm AS 195: Multivariate Normal Probabilities with Error Bound
- Dependence function for continuous bivariate densities
- A note on a goodness-of-fit test for the logistic regression model
- Association models and the bivariate normal for contingency tables with ordered categories
- Testing for dependence in multivariate probit models
- Existence and Uniqueness of the Maximum Likelihood Estimator for a Multivariate Probit Model
- Marginal Modeling of Correlated Ordinal Data Using a Multivariate Plackett Distribution
- The Grouped Continuous Model for Multivariate Ordered Categorical Variables and Covariate Adjustment
- Maximum Likelihood Estimation of Misspecified Models
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