To GEE or Not to GEE
Cancer Research And Biostatistics · University of California, Berkeley · +4 more institutions
Abstract
Two modeling approaches are commonly used to estimate the associations between neighborhood characteristics and individual-level health outcomes in multilevel studies (subjects within neighborhoods). Random effects models (or mixed models) use maximum likelihood estimation. Population average models typically use a generalized estimating equation (GEE) approach. These methods are used in place of basic regression approaches because the health of residents in the same neighborhood may be correlated, thus violating independence assumptions made by traditional regression procedures. This violation is particularly relevant to estimates of the variability of estimates. Though the literature appears to favor the…
Citation impact
- FWCI
- 30.65
- Percentile
- 100%
- References
- 25
Authors
8- AHAlan HubbardCorresponding
Cancer Research And Biostatistics, University of California, Berkeley
- JAJennifer Ahern
Berkeley Public Health Division, University of California, Berkeley
- NLNancy L. Fleischer
Berkeley Public Health Division, University of California, Berkeley
- MVMark van der Laan
Cancer Research And Biostatistics
- SASheri A. Lippman
Berkeley Public Health Division, University of California, Berkeley
Topics & keywords
- Gee
- Inference
- Econometrics
- Marginal model
- Generalized estimating equation
- Multilevel model
- Regression analysis
- Regression