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On estimation of linear transformation models with nested case–control sampling

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Abstract

Nested case–control (NCC) sampling is widely used in large epidemiological cohort studies for its cost effectiveness, but its data analysis primarily relies on the Cox proportional hazards model. In this paper, we consider a family of linear transformation models for analyzing NCC data and propose an inverse selection probability weighted estimating equation method for inference. Consistency and asymptotic normality of our estimators for regression coefficients are established. We show that the asymptotic variance has a closed analytic form and can be easily estimated. Numerical studies are conducted to support the theory and an application to the Wilms’ Tumor Study is also given to illustrate the methodology.

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Authors and Affiliations

  1. Department of Statistics, North Carolina State University, Raleigh, NC, 27695, USA

    Wenbin Lu

  2. Division of Biostatistics, New York University, New York, NY, 10016, USA

    Mengling Liu

Authors
  1. Wenbin Lu
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  2. Mengling Liu
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Correspondence to Wenbin Lu.

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Lu, W., Liu, M. On estimation of linear transformation models with nested case–control sampling. Lifetime Data Anal 18, 80–93 (2012). https://doi.org/10.1007/s10985-011-9203-3

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  • DOI: https://doi.org/10.1007/s10985-011-9203-3

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