title: Marginal models for longitudinal continuous proportional data.
abstract: Continuous proportional data arise when the response of interest is a percentage between zero and one, e.g., the percentage of decrease in renal function at different follow-up times from the baseline. In this paper, we propose methods to directly model the marginal means of the longitudinal proportional responses using the simplex distribution of Barndorff-Nielsen and Jørgensen that takes into account the fact that such responses are percentages restricted between zero and one and may as well have large dispersion. Parameters in such a marginal model are estimated using an extended version of the generalized estimating equations where the score vector is a nonlinear function of the observed response. The method is illustrated with an ophthalmology study on the use of intraocular gas in retinal repair surgeries.
authors.affiliation: Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada. song@pascal.math.yorku.ca
authors.forename: P X
authors.initials: PX
authors.lastname: Song
authors.forename: M
authors.initials: M
authors.lastname: Tan
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods; D005500:Follow-Up Studies; D005740:Gases / Q000627:therapeutic use; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D012164:Retinal Diseases / Q000601:surgery; D013997:Time Factors
chemical_list: D005740:Gases