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Marginal Models for Longitudinal Continuous Proportional Data
Author(s) -
Song Peter XueKun,
Tan Ming
Publication year - 2000
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2000.00496.x
Subject(s) - mathematics , zero (linguistics) , marginal model , simplex , longitudinal data , function (biology) , statistics , computer science , combinatorics , regression analysis , philosophy , linguistics , evolutionary biology , biology , data mining
Summary. 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.