What is it about?

We develop a new procedure for making simultaneous inference of the mCEP curve over a range of biomarker values, which utilizes the perturbation resampling method to approximate the asymptotic distribution of our estimator.

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Why is it important?

Making simultaneous inference about the mCEP curve is important for understanding biomarker-defined principal strata effect modification over a range of biomarker values but to our knowledge has not been addressed previously.


In this paper we have proposed a procedure for estimating the marginal CEP curve. We also developed procedures for obtaining pointwise and simultaneous confidence intervals about the marginal CEP curve via perturbation resampling. In addition, we have shown that pointwise and simultaneous interval estimates via perturbation resampling are more accurate and tighter than those obtained by the bootstrap, especially when the disease endpoint is rare.

Yingying Zhuang
University of Washington System

Read the Original

This page is a summary of: Simultaneous Inference of Treatment Effect Modification by Intermediate Response Endpoint Principal Strata with Application to Vaccine Trials, The International Journal of Biostatistics, July 2019, De Gruyter,
DOI: 10.1515/ijb-2018-0058.
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