title: Robust estimation of marginal regression parameters in clustered data.
abstract: We develop robust methods for analyzing clustered data where estimation of marginal regression parameters is of interest. Inverse cluster size reweighting in the objective function to be minimized is incorporated to handle the issue of informative cluster size. Performance of the resulting estimators is studied by simulation. Large sample inference and variance estimation is carried out. The methodology is illustrated using a periodontal disease dataset.
authors.affiliation: University of Louisville, Louisville, KY 40202, USA.
authors.forename: Somnath
authors.initials: S
authors.lastname: Datta
authors.affiliation: University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
authors.forename: James D
authors.initials: JD
authors.lastname: Beck
keywords: Informative cluster size; R estimator; dental data; random cluster size
references.citation: Biometrics. 2003 Mar;59(1):36-42
references.pmid: 12762439
references.citation: Stat Methods Med Res. 2011 Aug;20(4):347-67
references.pmid: 20223781
references.citation: J Periodontol. 1990 Aug;61(8):521-8
references.pmid: 2391631
references.citation: J Nonparametr Stat. 2012 Sep 1;24(3):797-808
references.pmid: 23074359
references.citation: Stat Pap (Berl). 2014 Feb 1;55(1):71-92
references.pmid: 25878396
references.citation: Biometrics. 2008 Mar;64(1):39-45
references.pmid: 17608784
references.citation: Biometrika. 2011 Mar;98(1):147-162
references.pmid: 23049125
references.citation: Biometrics. 2008 Jun;64(2):501-7
references.pmid: 17970820