Generalized methods of moments in marginal models for longitudinal data with time-dependent covariates.

Хэвлэлийн нэр: Journal of the Korean Data & Information Science Society

Зохиогч:  Д.Оюунчимэг

Хамтран зохиогч:

Хэвлүүлсэн огноо: 2013-07-31

Хуудас дугаар: 877-883

Өгүүллийн хураангуй:

The Quadratic inference functions (QIF) method proposed by Qu et al. (2000) and the Generalized method of moments (GMM) for marginal regression analysis of longitudinal data with time-dependent covariates proposed by Lai and Small (2007) both are the methods based on Generalized method of moment (GMM) introduced by Hansen (1982) and both use Generalized estimating equations (GEE). Lai and Small (2007) divided time-dependent covariates into three types such as: Type I, Type II and Type III.

In this paper, we compared these methods in the case of Type II and Type III in which full covariates conditional mean assumption (FCCM) is violated and interested in whether they can improve the results of GEE with independence working correlation. We show that in the marginal regression model with Type II time-dependent covariates, GMM Type II of Lai and Small (2007) provide more efficient result than QIF  and for the Type III time-dependent covariates, QIF with independence working correlation and GMM Type III methods provide the same re

Өгүүллийн төрөл: IEEE индекстэй сэтгүүл

Өгүүллийн зэрэглэл: Гадаад

Түлхүүр үг: #GEE #longitudinal data #FCCM assumption #QIF #time-dependent covariate. #GMM #marginal model

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