Criteria for Working–Correlation–Structure Selection in GEE

By Lin-Yee Hin, Vincent J. Carey, You‐Gan Wang. 2007

59 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3601e2d693028540b133e5a5b689d773cf4378ed

How researchers see this paper

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

In Management Science and Operations Research

1. Francis L. Huang
2. Daniel M. McNeish
3. Laura M. Stapleton
4. Daniel L. Oberski
5. T. Asparouhov
6. Mei-Shiu Chiu
7. Matthew A. Diemer
8. Michael T. Kalkbrenner

In Statistics and Probability

1. Francis L. Huang
2. Daniel M. McNeish
3. Laura M. Stapleton
4. R. Silverman
5. Milica Miočević
6. R. van de Schoot
7. Ji Seung Yang
8. S. Neuman

Citations in the corpus

• On the Unnecessary Ubiquity of Hierarchical Linear Modeling (2017, background): “However, Hin, Carey, and Wang (2007) noted that the Rotnizky-Jewell criterion (RJC) is more suitable for distinguishing between independent and exchangeable working structures.”
• Analyzing Cross-Sectionally Clustered Data Using Generalized Estimating Equations (2021, background): “As long though as the correlation (i.e., ICC) is not 0, then an exchangeable correlation structure may be the most reasonable because with “real life clustered data, working independence is nonexistent” (Hin et al., 2007, p. 364).”