Semiparametric inference for data with a continuous outcome from a two-phase probability-dependent sampling scheme
type="main" xml:id="rssb12029-abs-0001"> <title type="main">Summary</title> <p>Multiphased designs and biased sampling designs are two of the well-recognized approaches to enhance study efficiency. We propose a new and cost-effective sampling design, the two-phase probability-dependent sampling design, for studies with a continuous outcome. This design will enable investigators to make efficient use of resources by targeting more informative subjects for sampling. We develop a new semiparametric empirical likelihood inference method to take advantage of data obtained through a probability-dependent sampling design. Simulation study results indicate that the sampling scheme proposed, coupled with the proposed estimator, is more efficient and more powerful than the existing outcome-dependent sampling design and the simple random sampling design with the same sample size. We illustrate the method proposed with a real data set from an environmental epidemiologic study.
Year of publication: |
2014
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Authors: | Zhou, Haibo ; Xu, Wangli ; Zeng, Donglin ; Cai, Jianwen |
Published in: |
Journal of the Royal Statistical Society Series B. - Royal Statistical Society - RSS, ISSN 1369-7412. - Vol. 76.2014, 1, p. 197-215
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Publisher: |
Royal Statistical Society - RSS |
Saved in:
Online Resource
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