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Semiparametric two‐sample changepoint model with application to human immunodeficiency virus studies

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  • Zonghui Hu
  • Jing Qin
  • Dean Follmann

Abstract

Summary. A two‐sample changepoint model is proposed to investigate the difference between two treatments or devices. Under our semiparametric approach, no assumptions are made about the underlying distributions of the measurements from the two treatments or devices, but a parametric link is assumed between the two. The parametric link contains the possible changepoint where the two distributions start to differ. We apply the maximum empirical likelihood for model estimation and show the consistency of the changepoint estimator. An extended changepoint model is studied to handle data censored because of detection limits in viral load assays of human immunodeficiency virus (HIV). Permutation and bootstrap procedures are proposed to test the existence of a changepoint and the goodness of fit of the model. The performance of the semiparametric changepoint model is compared with that of parametric models in a simulation study. We provide two applications in HIV studies: one is a randomized placebo‐controlled study to evaluate the effects of a recombinant glycoprotein 120 vaccine on HIV viral load; the other is a study to compare two types of tubes in handling plasma samples for viral load determination.

Suggested Citation

  • Zonghui Hu & Jing Qin & Dean Follmann, 2008. "Semiparametric two‐sample changepoint model with application to human immunodeficiency virus studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(5), pages 589-607, December.
  • Handle: RePEc:bla:jorssc:v:57:y:2008:i:5:p:589-607
    DOI: 10.1111/j.1467-9876.2008.00632.x
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    References listed on IDEAS

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    1. Peter B. Gilbert & Ronald J. Bosch & Michael G. Hudgens, 2003. "Sensitivity Analysis for the Assessment of Causal Vaccine Effects on Viral Load in HIV Vaccine Trials," Biometrics, The International Biometric Society, vol. 59(3), pages 531-541, September.
    2. Zhong Guan, 2004. "A semiparametric changepoint model," Biometrika, Biometrika Trust, vol. 91(4), pages 849-862, December.
    3. Haitao Chu & Lawrence H. Moulton & Wendy J. Mack & Douglas J. Passaro & Paulo F. Barroso & Alvaro Muñoz, 2005. "Correlating two continuous variables subject to detection limits in the context of mixture distributions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 831-845, November.
    4. Dean A. Follmann & Michael A. Proschan, 1999. "A Multivariate Test of Interaction for Use in Clinical Trials," Biometrics, The International Biometric Society, vol. 55(4), pages 1151-1155, December.
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