This article considers analyzing longitudinal binary data semiparametrically and proposing GEE-Smoothing spline in the estimation of parametric and nonparametric components. The method is an extension of the parametric generalized estimating equation to semiparametric. The nonparametric component is estimated by smoothing spline approach, i.e., natural cubic spline. We use profile algorithm in the estimation of both parametric and nonparametric components. Properties of the estimators are evaluated by simulation
This paper considers nonparametric regression to analyze correlated data. The correlated data could ...
There have been studies on how the asymptotic efficiency of a nonparametric function estimator depen...
this paper is to simultaneously estimate n curves corrupted by noise, this means several observation...
This paper considers analyzing longitudinal data semiparametrically and proposing GEE-Smoothing spli...
In this paper we propose GEE‐Smoothing spline in the estimation of semiparametric models with correl...
This paper considers nonparametric regression to analyze longitudinal binary data. In this paper we ...
This paper proposes nonparametric regression model to analyze longitudinal data. We combine natural ...
This paper considers performance of some smoothing parameter selection methods in Generalized Estima...
Longitudinal data frequently arises in various fields of applied sciences where individuals are meas...
This paper considers a method to analyze semiparametric binary models for clustered survival data wh...
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric e...
this paper provides the mechanism for including cubic smoothing splines in models for the analysis o...
Semiparametric additive regression model is a combination of parametric and nonparametric regression...
We consider nonparametric regression in a longitudinal marginal model of generalized estimating equa...
We consider the applicability of smoothing splines via the penalized likelihood method to large data...
This paper considers nonparametric regression to analyze correlated data. The correlated data could ...
There have been studies on how the asymptotic efficiency of a nonparametric function estimator depen...
this paper is to simultaneously estimate n curves corrupted by noise, this means several observation...
This paper considers analyzing longitudinal data semiparametrically and proposing GEE-Smoothing spli...
In this paper we propose GEE‐Smoothing spline in the estimation of semiparametric models with correl...
This paper considers nonparametric regression to analyze longitudinal binary data. In this paper we ...
This paper proposes nonparametric regression model to analyze longitudinal data. We combine natural ...
This paper considers performance of some smoothing parameter selection methods in Generalized Estima...
Longitudinal data frequently arises in various fields of applied sciences where individuals are meas...
This paper considers a method to analyze semiparametric binary models for clustered survival data wh...
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric e...
this paper provides the mechanism for including cubic smoothing splines in models for the analysis o...
Semiparametric additive regression model is a combination of parametric and nonparametric regression...
We consider nonparametric regression in a longitudinal marginal model of generalized estimating equa...
We consider the applicability of smoothing splines via the penalized likelihood method to large data...
This paper considers nonparametric regression to analyze correlated data. The correlated data could ...
There have been studies on how the asymptotic efficiency of a nonparametric function estimator depen...
this paper is to simultaneously estimate n curves corrupted by noise, this means several observation...