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Biometrics
Article . 2015 . Peer-reviewed
License: OUP Standard Publication Reuse
Data sources: Crossref
Biometrics
Article . 2016
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Rejoinder to “On the Misuse of Taylor Expansion”

Authors: Shanshan, Zhao; Ross L, Prentice;

Rejoinder to “On the Misuse of Taylor Expansion”

Abstract

Abstract This article is the rejoinder to: The authors replied as follows: We thank Drs Wang, Zhang, Feng, and Tu for pointing out a missing op(1) term in a Taylor expansion in Theorem 2 of Supplementary Materials to Zhao and Prentice (2014), an omission that apparently occurred also in several earlier statistical publications (Feng et al., 2013). However, the estimating function in our Theorem 2 is unbiased and our use of this expansion was solely for the purpose of developing the asymptotic distribution for the solution to this estimating equation, which is unaffected by the missing op(1) term. Shanshan Zhao and Ross L. Prentice Public Health Sciences Division Fred Hutchinson Cancer Research Center Seattle, Washington 98109, U.S.S.

Keywords

Postmenopause, Hormone Replacement Therapy, Humans, Breast Neoplasms, Female, Artifacts, Algorithms, Proportional Hazards Models

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid
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Cancer Research