Semiparametric regression in size-biased sampling.
Semiparametric regression in size-biased sampling.
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DOI:
10.1111/j.1541-0420.2009.01260.x
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发表时间:
2010-03
期刊:
影响因子:
1.9
通讯作者:
Chen YQ
中科院分区:
文献类型:
--
作者:
Chen YQ
Size-biased sampling arises when a positive-valued outcome variable is sampled with selection probability proportional to its size. In this article, we propose a semiparametric linear regression model to analyze size-biased outcomes. In our proposed model, the regression parameters of the covariates are of major interest, while the distribution of random errors is unspecified. Under the proposed model, we discover that the regression parameters are invariant regardless of size-biased sampling. Following this invariance property, we develop a simple estimation procedure for inferences. Our proposed methods are evaluated in simulation studies and applied to two real data analyses.
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