A Correlated Probit Model for Joint Modeling of Clustered Binary and Continuous Responses

By Ralitza Gueorguieva, Alan Agresti. 2001

183 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/bc5c84a861be8568848398ff8eb46c2e35826db6

How researchers see this paper

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In Statistics and Probability

1. Peter S. Craig
2. Xuefeng Liu
3. Michael J. Daniels
4. Chandra R. Bhat
5. Mohsen Pourahmadi
6. Jarrod Hadeld
7. Zdravko I. Botev
8. Geert Molenberghs

Citations in the corpus

• A new reconstruction of multivariate normal orthant probabilities (2007, methodology): “Moreover, from an applied viewpoint, the cumulative distribution function is a fundamental component of the multivariate probit models that were applied by Chib and Greenberg (1998), Gueorguieva and Agresti (2001), Papathomas and O’Hagan (2005) and others, where efficient computation is important.”
• A New Algorithm for Simulating a Correlation Matrix Based on Parameter Expansion and Reparameterization (2006, methodology): “…regression (Barnard, McCulloch, and Meng 2001), scale mixtures of multivariate normal link models (Chen and Dey 1998, 2000) and joint models for longitudinal binary and continuous responses (Gueorguieva and Agresti 2001); for the final case, the PX-RPMH algorithm has been implemented (Liu 2006).”