TITLE:
A Recursive Binary Tree Model for the Analysis of the Response to Antiretroviral Therapy of HIV Infected Adults in Burkina Faso
AUTHORS:
Simon Tiendrébéogo, Séni Kouanda, Blaise Somé, Simplice Dossou-Gbeté
KEYWORDS:
Model-Based Conditional Regression Tree, CD4 Cell Count Prediction, Linear Mixed Model, Stability Analysis, Antiretroviral Therapy
JOURNAL NAME:
Open Journal of Statistics,
Vol.9 No.6,
November
28,
2019
ABSTRACT: In this paper we aim to analyse temporal variation of CD4 cell counts for
HIV-infected individuals under antiretroviral therapy by using statistical
methods. This is achieved by resorting to recursive binary regression tree approach [1][2]. This approach has made it possible to highlight the existence of
several segments of the population of interest described by the interactions
between the predictive covariates of the response to the treatment regimen.