Advanced search
Publication Cover
Ophthalmic Epidemiology Volume 30, 2023 - Issue 3
Submit an article Journal homepage
405
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Comparing Generalized Estimating Equation and Linear Mixed Effects Model for Estimating Marginal Association with Bivariate Continuous Outcomes

Mingyi Lia Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USAView further author information
&
Xiangrong Konga Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA;b Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltiomre, Maryland, USA;c Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health;d Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public HealthCorrespondence[email protected]
View further author information
Pages 307-316 | Received 25 Oct 2021, Accepted 04 Jul 2022, Published online: 15 Jul 2022

References

  • Ying GS, Maguire MG, Glynn R, Rosner B. Tutorial on biostatistics: statistical analysis for correlated binary eye data. Ophthalmic Epidemiol. 2018;25(1):1–12. doi:10.1080/09286586.2017.1320413.
  • Glynn R, Rosner B. Regression methods when the eye is the unit of analysis. Ophthalmic Epidemiol. 2012;19(3):159–165. doi:10.3109/09286586.2012.674614.
  • Glynn R, Rosner B. Accounting for the correlation between fellow eyes in regression analysis. Arch Ophthalmol. 1992;110(3):381–387. doi:10.1001/archopht.1992.01080150079033.
  • Ying GS, Maguire MG, Glynn R, Rosner B. Tutorial on biostatistics: linear regression analysis of continuous correlated eye data. Ophthalmic Epidemiol. 2017;24(2):130–140. doi:10.1080/09286586.2016.1259636.
  • Zeger SL, Liang KY, Albert PS. Models for longitudinal data: a generalized estimating equation approach. Biometrics. 1988;44(4):1049–1060. doi:10.2307/2531734.
  • Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics. 1982;38(4):963. doi:10.2307/2529876.
  • Campochiaro PA, Iftikhar M, Hafiz G, et al. Oral N-acetylcysteine improves cone function in retinitis pigmentosa patients in phase I trial. J Clin Invest. 2020;130(3):1527–1541. doi:10.1172/JCI132990.
  • Rosner B, Glynn R. Estimation of rank correlation for clustered data. Stat Med. 2017;36(14):2163–2186. doi:10.1002/sim.7257.
  • Liang KY, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika. 1986;73(1):13–22. doi:10.1093/biomet/73.1.13.
  • SAS Institute Inc. SAS/STAT® 15.1 User’s Guide. Cary, NC: SAS Institute Inc; 2018.
  • Patterson HD, Thompson R. Recovery of inter-block information when block sizes are unequal. Biometrika. 1971;58(3):545–554. doi:10.1093/biomet/58.3.545.
  • Stroup WW. Part II: estimation and Inference Essentials. In: Dominici FJFTZ, ed. Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. Boca Raton, FL: Taylor & Francis Group, LLC; 2013:131–139.
  • Johnson RW. An Introduction to the Bootstrap. Teach Stat. 2001;23:2. doi:10.1111/1467-9639.00050.
  • Imbens GW, Kolesár M. Robust standard errors in small samples: some practical advice. Rev Econ Stat. 2016;98(4):701–712. doi:10.1162/REST_a_00552.
  • Hubbard AE, Ahern J, Fleischer NL, et al. To GEE or Not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health. Source Epidemiol 2016;21(4):467–474. Doi:10.1097/EDE.ObOl
  • Paul S, Zhang X. Small sample GEE estimation of regression parameters for longitudinal data. Stat Med. 2014;33(22):3869–3881. doi:10.1002/sim.6198.
  • Auda HA, McKean JW, Kloke JD, Sadek M, Monte A. Carlo study of REML and robust rank-based analyses for the random intercept mixed model. Commun Stat Simul Comput. 2019;48(3):837–860. doi:10.1080/03610918.2017.1400561.
  • Fellingham GW, Raghunathan TE. Sensitivity of point and interval estimates to distributional assumptions in longitudinal data analysis of small samples. Commun Stat - Simul Comput. 1995;24(3):617–630. doi:10.1080/03610919508813263.
  • Pinheiro J, Bates D, DebRoy S, Sarkar D. {R Core Team}. {nlme}: linear and Nonlinear Mixed Effects Models. R Package Version. 2021:3.1–152.
  • Halekoh U, Højsgaard S, Yan J. The R package geepack for generalized estimating equations. J Stat Softw. 2006;15(2):1–11. doi:10.18637/jss.v015.i02.
  • Zorn CJW. Generalized estimating equation models for correlated data: a review with applications. Am J Pol Sci. 2001;45(2):470. doi:10.2307/2669353.
  • Ballinger GA. Using generalized estimating equations for longitudinal data analysis. Organ Res Methods. 2004;7(2):127–150. doi:10.1177/1094428104263672.
  • Society IB. A Caveat Concerning. Independence estimating equations with multivariate binary data. Biometrics. 2010;51(1): 309–317.
  • Huang J, Huang J, Chen Y, Ying GS. Evaluation of approaches to analyzing continuous correlated eye data when sample size is small. Ophthalmic Epidemiol. 2018;25(1):45–54. doi:10.1080/09286586.2017.1339809.
  • Stroup WW. Part I: the Big Picture. In: Dominici FJFTZ, ed. Generalized Linear Mixed Models: Modern Concepts, Methods and Applications. Boca Raton, FL: Taylor & Francis Group, LLC; 2013:65–71.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.