Modeling Clustered Ordered Categorical Data: A Survey

By Alan Agresti, R. Natarajan. 2001

108 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e6e7a15f8f18ba6ac49f6b38a99733dcf60b6779

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

1. Maria Iannario
2. Donald Hedeker
3. Sophia Rabe-Hesketh
4. A. Skrondal

Citations in the corpus

• Hierarchical CUB Models for Ordinal Variables (2012, background): “As a final remark, we notice how multilevel paradigm is particularly useful for longitudinal studies where the role of subjects and clusters is reversed (Agresti and Natarajan, 2001).”
• Multilevel Models for Ordinal and Nominal Variables (2008, background): “Again, developments have been mainly in terms of logistic and probit regression models, and many of these are reviewed in Agresti and Natarajan [5].”
• An Introduction to Growth Modeling (2004, unknown): “Most of these articles concern continuous response variables, although ones dealing specifically with categorical outcomes have also appeared (Agresti & Natarajan, 2001; Fitzmaurice, Laird, & Rotnitzky, 1993; Gibbons & Hedeker, 1994; Hedeker & Mermelstein, 1996, 2000; Pendergast et al., 1996; Zeger…”