Resumo

SOSA, JUAN CAMILO  e  DIAZ, LUIS GUILLERMO. Time-Varying Coefficient Model Component Estimation Through Generalized Estimation Equations. Rev.Colomb.Estad. [online]. 2010, vol.33, n.1, pp.89-109. ISSN 0120-1751.

A methodology to estimate time-varying coefficient models components through generalized estimation equations (Liang & Zeger 1986) is proposed, in order to include directly in the estimation the possible correlation between repeated measurements of each subject. Expansion of the time-varying coefficients is done by means of regression spline methods (Huang et al. 2002). Furthermore, is proposed the use of the Akaikes information criterion in generalized estimating equations (QIC) proposed by Pan (2001) like model selector. Through simulation are compared the proposed methodology and the methodology presented by Wu & Zhang (2006), where models components are estimated through weighted least squares and Akaikes information criterion (AIC) is used like model selector. It resulted that the proposed methodology gives a better behavior in relation with the average mean square error. In order to illustrate the methodology, is taken into account the data base ACTG 315 (Liang et al. 2003) related to a AIDS study, where it is investigated the relationship between the viral charge and the CD4+ cell count.

Palavras-chave : AIC; Generalized estimation equations; Regression spline; Longitudinal data; Time-varying coefficient model; Weighted least squares.

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