Title : ( Multicollinearity and Linear Predictor Link Function Problems in Regression Modelling of Longitudinal Data )
Authors: , Mohammad Arashi , Manda S ,
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Abstract
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.
Keywords
generalized estimating equations; longitudinal data; multicollinearity; partially generalized linear models; ridge regression
@article{paperid:1093063,
author = {, and Arashi, Mohammad and ماندا، س},
title = {Multicollinearity and Linear Predictor Link Function Problems in Regression Modelling of Longitudinal Data},
journal = {Mathematics},
year = {2023},
volume = {11},
number = {3},
month = {January},
issn = {2227-7390},
pages = {530--530},
numpages = {0},
keywords = {generalized estimating equations; longitudinal data; multicollinearity; partially generalized linear models; ridge regression},
}
%0 Journal Article
%T Multicollinearity and Linear Predictor Link Function Problems in Regression Modelling of Longitudinal Data
%A ,
%A Arashi, Mohammad
%A ماندا، س
%J Mathematics
%@ 2227-7390
%D 2023
