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The Analysis of Bivariate Truncated Data Using the Clayton Copula Model

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  • Wang Antai

    (Georgetown University)

Abstract

In individuals infected with human immunodeficiency virus (HIV), distributions of quantitative HIV RNA measurements may be highly left-censored due to values falling below assay detection limits (DL). It is of the interest to find the relationship between plasma and semen viral loads. To address this type of problem, we developed an empirical goodness-of-fit test to check the Clayton model assumption for bivariate truncated data. We also used truncated tau to estimate the dependence parameter in the Clayton model for this type of data. It turns out that the proposed methodology works for both truncated and fixed left censored bivariate data. The proposed test procedure is demonstrated using an HIV data set, and statistical inference is drawn based on corresponding test result.

Suggested Citation

  • Wang Antai, 2007. "The Analysis of Bivariate Truncated Data Using the Clayton Copula Model," The International Journal of Biostatistics, De Gruyter, vol. 3(1), pages 1-18, April.
    • Handle: RePEc:bpj:ijbist:v:3:y:2007:i:1:n:8
    DOI: 10.2202/1557-4679.1050
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    Cited by:

    1. Wang, Antai, 2008. "A note on checking the Clayton model assumption based on left-truncated bivariate data," Statistics & Probability Letters, Elsevier, vol. 78(10), pages 1168-1173, August.
    2. Cheng Yu, 2009. "Modeling Cumulative Incidences of Dementia and Dementia-Free Death Using a Novel Three-Parameter Logistic Function," The International Journal of Biostatistics, De Gruyter, vol. 5(1), pages 1-19, November.

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