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A Recursive Binary Tree Model for the Analysis of the Response to Antiretroviral Therapy of HIV Infected Adults in Burkina Faso
Laboratoire d’Analyse Numérique, d’Informatique et de BIOmathématiques, Université Ouaga I Pr Joseph KI ZERBO, Ouagadougou, Burkina Faso
Département Biomédical et Santé Publique, Institut de Recherche en Sciences de la Santé, Ouagadougou, Burkina Faso
Laboratoire d’Analyse Numérique, d’Informatique et de BIOmathématiques, Université Ouaga I Pr Joseph KI ZERBO, Ouagadougou, Burkina Faso
Université de Pau et des Pays de l’Adour, E2S UPPA, CNRS, LMAP, Pau, France
- 1 Laboratoire d’Analyse Numérique, d’Informatique et de BIOmathématiques, Université Ouaga I Pr Joseph KI ZERBO, Ouagadougou, Burkina Faso
- 2 Département Biomédical et Santé Publique, Institut de Recherche en Sciences de la Santé, Ouagadougou, Burkina Faso
- 3 Laboratoire d’Analyse Numérique, d’Informatique et de BIOmathématiques, Université Ouaga I Pr Joseph KI ZERBO, Ouagadougou, Burkina Faso
- 4 Université de Pau et des Pays de l’Adour, E2S UPPA, CNRS, LMAP, Pau, France
Open Journal of Statistics·Volume 09 (2019)·Pages 643–656·Published 25 November 2019·DOI10.4236/ojs.2019.96041
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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.
KeywordsModel-Based Conditional Regression TreeCD4 Cell Count PredictionLinear Mixed ModelStability AnalysisAntiretroviral Therapy
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