Recent Studies on Regularization Methods in
Semiparametric Models with Longitudinal Data

Omidali Aghababaei Jazi

Mini Review

Recent Studies on Regularization Methods in Semiparametric Models with Longitudinal Data

Omidali Aghababaei Jazi*

Department of Mathematical and Computational Sciences, University of Toronto Mississauga

Corresponding Author

Received Date:November 3, 2022; Published Date:November 18, 2022

Abstract

Longitudinal data arise when an outcome variable is measured on the same subjects on several occasions. Semiparametric regression models are commonly used for modelling of longitudinal data as they provide more flexibility in studying the association between regression factors and a longitudinal outcome. Regularization methods for these models have received much attention over the last two decades in order to reduce the complexity of the models and improve their predictability. In this short article, I will review recent studies on regularization methods in semiparametric models with longitudinal data.

Keywords:Longitudinal data; Regularization; Semiparametric models; Informative follow-up

Article Details

Citation

Omidali Aghababaei Jazi*. Recent Studies on Regularization Methods in Semiparametric Models with Longitudinal Data. Annal Biostat & Biomed Appli. 4(5): 2022. ABBA.MS.ID.000598.