Published

2010-01-01

ESTIMACIÓN DE LAS COMPONENTES DE UN MODELO DE COEFICIENTES DINÁMICOS MEDIANTE LAS ECUACIONES DE ESTIMACIÓN GENERALIZADAS

TIME-VARYING COEFFICIENT MODEL COMPONENT ESTIMATION THROUGH GENERALIZED ESTIMATION EQUATIONS

Keywords:

criterio de información de Akaike, ecuaciones de estimación generalizadas, mínimos cuadrados ponderados, modelo de coeficientes dinámicos, regresión spline (es)
AIC, Generalized estimation equations, Regression spline, Longitudinal data, Time-varying coefficient model, Weighted least squares (en)

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Authors

  • Juan Camilo Sosa Universidad Nacional de Colombia
  • Luis Guillermo Díaz Universidad Nacional de Colombia
Se propone una metodología para estimar las componentes de un modelo de coeficientes dinámicos mediante las ecuaciones de estimación generalizadas (Liang & Zeger 1986), con el propósito de incluir directamente en la estimación la posible correlación de las medidas repetidas de cada individuo. La expansión de los coeficientes dinámicos del modelo se lleva a cabo a través de regresión spline (Huang et al. 2002). También se propone utilizar el criterio de información de Akaike en las ecuaciones de estimación generalizadas (QIC) (Pan 2001) como selector de modelos. Mediante simulación se compara la metodología propuesta con la metodología presentada por Wu & Zhang (2006), donde se estiman las componentes del modelo mediante mínimos cuadrados ponderados y se utiliza el criterio de información de Akaike (AIC) como selector de modelos, obteniéndose que en los escenarios simulados la metodología propuesta presenta mejores resultados con relación al error cuadrático medio promedio. Para ilustrar la estrategia de estimación propuesta, se considera el conjunto de datos ACTG 315 (Liang et al. 2003) asociado con un estudio de sida, en el que se modela dinámicamente la relación entre la carga viral y el conteo de células CD4+.
A methodology to estimate time-varying coefficient model’s 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 Akaike’s 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 model’s components are estimated through weighted least squares and Akaike’s 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.

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How to Cite

Sosa, J. C., & Díaz, L. G. (2010). TIME-VARYING COEFFICIENT MODEL COMPONENT ESTIMATION THROUGH GENERALIZED ESTIMATION EQUATIONS. Revista Colombiana De Estadística, 33(1), 89-109. https://revistas.unal.edu.co/index.php/estad/article/view/29811

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