Efficiency of generalized estimating equations for binary responses

By N. Rao Chaganty, Harry Joe. 2004

110 citations recorded by the source corpus.

Subfields: Food Science, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d3b294383729e927d764c4e3647d4e0a44f0450d

How researchers see this paper

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

In Food Science

1. Søren Højsgaard
2. U. Halekoh
3. Lan Wang
4. Jun Yan

In Management Science and Operations Research

1. Søren Højsgaard
2. U. Halekoh
3. Lan Wang
4. Jun Yan

In Statistics and Probability

1. Søren Højsgaard
2. U. Halekoh
3. Lan Wang
4. Jun Yan
5. Francis L. Huang
6. Peter C. Austin
7. Subir Ghosh
8. Steven G. Luke

Citations in the corpus

• GEE analysis of clustered binary data with diverging number of covariates (2011, background): “Thus, R ( τ ) should be understood as a weight matrix [Chaganty and Joe (2004)].”
• The R Package geepack for Generalized Estimating Equations (2005, methodology): “Using a fixed working correlation ( corstr="fixed" ) may still yield efficient estimates (Chaganty and Joe 2004) for β .”
• Generalized Estimating Equations in Longitudinal Data Analysis: A Review and Recent Developments (2014, unknown): “also discussed the covariate selection for longitudinal data analysis [46]; also, a variance function selection was mentioned by Pan and Mackenzie [30] as well as Wang and Lin [47]; in addition, more work on “working” correlation structure selection was addressed by Chaganty and Joe [48], Wang and L”