In the longitudinal data analysis we integrate flexible linear predictor link function and high-correlated predictor variables. Our approach uses B-splines for non-parametric part in the linear predictor component. A generalized estimation equation is used to estimate the parameters of the proposed model. We assess the performance of our proposed model using simulations and an application to an analysis of acquired immunodeficiency syndrome data set
This paper considers analyzing longitudinal data semiparametrically and proposing GEE-Smoothing spli...
AbstractIn this paper, we focus on single-index models for longitudinal data. We propose a procedure...
Poster presented at the Workshop on Flexible Models for Longitudinal and Survival Data with Applicat...
This paper proposes nonparametric regression model to analyze longitudinal data. We combine natural ...
A penalized spline approximation is proposed in considering nonparametric regression for longitudina...
Linear mixed effects methods for the analysis of longitudinal data provide a convenient framework fo...
175 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.A general description of line...
Generalized linear models (GLMs) outline a wide class of regression models where the effect of the e...
In classification problems where the predictor variables are longitudinal, classical linear dis-crim...
The authors consider regression analysis for binary data collected repeatedly over time on members o...
In regression models for categorical data a linear model is typically related to the response variab...
In this thesis, we investigate new methods, extending the marginal and mixed effects models to deal ...
In many studies the association of longitudinal measurements of a continuous response and a primary ...
This paper proposes an extension of generalized linear models to the analysis of longitudinal data. ...
Improving efficiency for regression coefficients and predicting trajectories of individuals are two ...
This paper considers analyzing longitudinal data semiparametrically and proposing GEE-Smoothing spli...
AbstractIn this paper, we focus on single-index models for longitudinal data. We propose a procedure...
Poster presented at the Workshop on Flexible Models for Longitudinal and Survival Data with Applicat...
This paper proposes nonparametric regression model to analyze longitudinal data. We combine natural ...
A penalized spline approximation is proposed in considering nonparametric regression for longitudina...
Linear mixed effects methods for the analysis of longitudinal data provide a convenient framework fo...
175 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.A general description of line...
Generalized linear models (GLMs) outline a wide class of regression models where the effect of the e...
In classification problems where the predictor variables are longitudinal, classical linear dis-crim...
The authors consider regression analysis for binary data collected repeatedly over time on members o...
In regression models for categorical data a linear model is typically related to the response variab...
In this thesis, we investigate new methods, extending the marginal and mixed effects models to deal ...
In many studies the association of longitudinal measurements of a continuous response and a primary ...
This paper proposes an extension of generalized linear models to the analysis of longitudinal data. ...
Improving efficiency for regression coefficients and predicting trajectories of individuals are two ...
This paper considers analyzing longitudinal data semiparametrically and proposing GEE-Smoothing spli...
AbstractIn this paper, we focus on single-index models for longitudinal data. We propose a procedure...
Poster presented at the Workshop on Flexible Models for Longitudinal and Survival Data with Applicat...