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

作者：Kim Jane Paik^*; Lu Wenbin; Sit Tony; Ying Zhiliang

来源：Journal of the American Statistical Association, 2013, 108(501): 217-227.

DOI：10.1080/01621459.2012.746073

• Case-cohort design
• Counting process
• Cox model
• Estimating equations
• Importance sampling
• Length bias
• Proportional odds model
• Regression
• Survival data
• Truncation

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.

• 出版日期2013-3