A Unified Approach to Semiparametric Transformation Models Under General Biased Sampling Schemes

Jane Paik Kim, Wenbin Lu, Tony Sit and Zhiliang Ying

Journal of the American Statistical Association, 2013, vol. 108, issue 501, 217-227

Abstract: We propose a unified estimation method for semiparametric linear transformation models under general biased sampling schemes. The new estimator is obtained from a set of counting process-based unbiased estimating equations, developed through introducing a general weighting scheme that offsets the sampling bias. The usual asymptotic properties, including consistency and asymptotic normality, are established under suitable regularity conditions. A closed-form formula is derived for the limiting variance and the plug-in estimator is shown to be consistent. We demonstrate the unified approach through the special cases of left truncation, length bias, the case-cohort design, and variants thereof. Simulation studies and applications to real datasets are presented.

Date: 2013
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Citations: View citations in EconPapers (9)

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DOI: 10.1080/01621459.2012.746073

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