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Confidence intervals for a common mean with missing data with applications in an AIDS study

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  • Liang, Hua
  • Su, Haiyan
  • Zou, Guohua

Abstract

In practical data analysis, nonresponse phenomenon frequently occurs. In this paper, we propose an empirical likelihood based confidence interval for a common mean by combining the imputed data, assuming that data are missing completely at random. Simulation studies show that such confidence intervals perform well, even when the missing proportion is high. Our method is applied to an analysis of a real data set from an AIDS clinic trial study.

Suggested Citation

  • Liang, Hua & Su, Haiyan & Zou, Guohua, 2008. "Confidence intervals for a common mean with missing data with applications in an AIDS study," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 546-553, December.
    • Handle: RePEc:eee:csdana:v:53:y:2008:i:2:p:546-553
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    References listed on IDEAS

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    1. Liang H. & Wang S. & Robins J.M. & Carroll R.J., 2004. "Estimation in Partially Linear Models With Missing Covariates," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 357-367, January.
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    5. Joseph G. Ibrahim & Ming-Hui Chen & Stuart R. Lipsitz, 1999. "Monte Carlo EM for Missing Covariates in Parametric Regression Models," Biometrics, The International Biometric Society, vol. 55(2), pages 591-596, June.
    6. Song Chen, 1993. "On the accuracy of empirical likelihood confidence regions for linear regression model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(4), pages 621-637, December.
    7. Lang Wu, 2004. "Exact and Approximate Inferences for Nonlinear Mixed-Effects Models With Missing Covariates," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 700-709, January.
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    Cited by:

    1. Bindele, Huybrechts F. & Abebe, Ash, 2015. "Semi-parametric rank regression with missing responses," Journal of Multivariate Analysis, Elsevier, vol. 142(C), pages 117-132.

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