Comparison of viral trajectories in aids studies by using nonparametric mixed-effects models

Chin-Shang Li, Hua Liang, Ying Hen Hsieh, Shiing Jer Twu

Research output: Contribution to journalArticlepeer-review

Abstract

The efficacy of antiretroviral therapies for human immunodeficiency virus (HIV) infection can be assessed by studying the trajectory of the changing viral load with treatment time, but estimation of viral trajectory parameters by using the implicit function form of linear and nonlinear parametric models can be problematic. Using longitudinal viral load data from a clinical study of HIV-infected patients in Taiwan, we described the viral trajectories by applying a nonparametric mixed-effects model. We were then able to compare the efficacies of highly active antiretroviral therapy (HAART) and conventional therapy by using Young and Bowman's (1995) test.

Original languageEnglish (US)
Pages (from-to)443-450
Number of pages8
JournalJournal of Modern Applied Statistical Methods
Volume2
Issue number2
StatePublished - 2003
Externally publishedYes

Keywords

  • Aids clinical trial
  • HIV dynamics
  • Kernel regression
  • Longitudinal data
  • Nonparametric mixed-effects model
  • Viral load trajectory

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

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