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Sliced inverse regression for survival data

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  • Maya Shevlyakova
  • Stephan Morgenthaler

Abstract

We apply the univariate sliced inverse regression to survival data. Our approach is different from the other papers on this subject. The right-censored observations are taken into account during the slicing of the survival times by assigning each of them with equal weight to all of the slices with longer survival. We test this method with different distributions for the two main survival data models, the accelerated lifetime model and Cox’s proportional hazards model. In both cases and under different conditions of sparsity, sample size and dimension of parameters, this non-parametric approach finds the data structure and can be viewed as a variable selector. Copyright Springer-Verlag Berlin Heidelberg 2014

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  • Maya Shevlyakova & Stephan Morgenthaler, 2014. "Sliced inverse regression for survival data," Statistical Papers, Springer, vol. 55(1), pages 209-220, February.
    • Handle: RePEc:spr:stpapr:v:55:y:2014:i:1:p:209-220
    DOI: 10.1007/s00362-013-0552-8
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    References listed on IDEAS

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    1. Li, Lexin & Lu, Wenbin, 2008. "Sufficient Dimension Reduction With Missing Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 822-831, June.
    2. Wenbin Lu & Lexin Li, 2011. "Sufficient Dimension Reduction for Censored Regressions," Biometrics, The International Biometric Society, vol. 67(2), pages 513-523, June.
    3. Cook, R. Dennis & Ni, Liqiang, 2005. "Sufficient Dimension Reduction via Inverse Regression: A Minimum Discrepancy Approach," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 410-428, June.
    4. Nadkarni, Nivedita V. & Zhao, Yingqi & Kosorok, Michael R., 2011. "Inverse Regression Estimation for Censored Data," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 178-190.
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    Cited by:

    1. Huiwen Wang & Zhichao Wang & Shanshan Wang, 2021. "Sliced inverse regression method for multivariate compositional data modeling," Statistical Papers, Springer, vol. 62(1), pages 361-393, February.

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