To GEE or Not to GEE: Comparing Population Average and Mixed Models for Estimating the Associations Between Neighborhood Risk Factors and Health

By Alan E. Hubbard, J. Ahern, N. Fleischer, M. J. van der Laan, Sheri A. Lippman, Nicholas P. Jewell, T. Bruckner, W. Satariano. Epidemiology, 2010

1,086 citations recorded by the source corpus.

Subfields: Health, Sociology and Political Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b57690e255a452e7c1c20cd273a7ac791f774420

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In Health

1. Francis L. Huang

In Sociology and Political Science

1. Francis L. Huang

In Statistics and Probability

1. Francis L. Huang
2. Pier Vittorio Mannucci
3. Kevyn Yong

Citations in the corpus

• The Differential Impact of Knowledge Depth and Knowledge Breadth on Creativity over Individual Careers (2017, background): “While GEE is robust to misspecifications of the underlying correlation structures (Hubbard et al., 2010), it might be that nesting makes estimations inefficient.”
• Analyzing Cross-Sectionally Clustered Data Using Generalized Estimating Equations (2021, methodology): “Inferential statistical tests however do not differ much when using a PA or CS approach (Agresti, 2007), and several articles have discussed the differences between the PA and CS approaches (Fieberg et al., 2009; Hubbard et al., 2010; Subramanian & O’Malley, 2010).”
• On the Unnecessary Ubiquity of Hierarchical Linear Modeling (2017, neutral): “…Ballinger, 2004; Burton, Gurrin, & Sly, 1998; Gardiner, Luo, & Roman, 2009; Ghisletta & Spini, 2004; Hanley, Negassa, Edwardes, & Forrester, 2003; Hubbard et al., 2010; Twisk, 2004; Zorn, 2001), but, as argued throughout this article, they are not targeted toward psychologists, and psychologists…”