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Modelling longitudinal semicontinuous emesis volume data with serial correlation in an acupuncture clinical trial

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  • Paul S. Albert
  • Joannie Shen

Abstract

Summary. In longitudinal studies, we are often interested in modelling repeated assessments of volume over time. Our motivating example is an acupuncture clinical trial in which we compare the effects of active acupuncture, sham acupuncture and standard medical care on chemotherapy‐induced nausea in patients being treated for advanced stage breast cancer. An important end point for this study was the daily measurement of the volume of emesis over a 14‐day follow‐up period. The repeated volume data contained many 0s, had apparent serial correlation and had missing observations, making analysis challenging. The paper proposes a two‐part latent process model for analysing the emesis volume data which addresses these challenges. We propose a Monte Carlo EM algorithm for parameter estimation and we use this methodology to show the beneficial effects of acupuncture on reducing the volume of emesis in women being treated for breast cancer with chemotherapy. Through simulations, we demonstrate the importance of correctly modelling the serial correlation for making conditional inference. Further, we show that the correct model for the correlation structure is less important for making correct inference on marginal means.

Suggested Citation

  • Paul S. Albert & Joannie Shen, 2005. "Modelling longitudinal semicontinuous emesis volume data with serial correlation in an acupuncture clinical trial," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(4), pages 707-720, August.
    • Handle: RePEc:bla:jorssc:v:54:y:2005:i:4:p:707-720
    DOI: 10.1111/j.1467-9876.2005.05515.x
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    Cited by:

    1. Brian J. Reich & Montserrat Fuentes & Amy H. Herring & Kelly R. Evenson, 2010. "Bayesian Variable Selection for Multivariate Spatially Varying Coefficient Regression," Biometrics, The International Biometric Society, vol. 66(3), pages 772-782, September.
    2. Ghosh, Pulak & Albert, Paul S., 2009. "A Bayesian analysis for longitudinal semicontinuous data with an application to an acupuncture clinical trial," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 699-706, January.
    3. Yang, Yan & Simpson, Douglas, 2010. "Unified computational methods for regression analysis of zero-inflated and bound-inflated data," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1525-1534, June.

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