A quadratic bootstrap method and improved estimation in logistic regression

Gerda Claeskens, Marc Aerts and Geert Molenberghs

Statistics & Probability Letters, 2003, vol. 61, issue 4, 383-394

Abstract: This paper presents a quadratic one-step bootstrap method for binary response data. Rather than resampling from the original sample, the proposed method resamples summands appearing in the quadratic approximation of the estimates. It enjoys the same computational simplicity as its linear analogue while being more accurate. Moreover it allows the construction of a bias corrected estimator and improved confidence intervals. A small simulation study illustrates the improved finite sample behaviour for binary response data.

Keywords: Bias; correction; Bootstrap; confidence; interval; One-step; bootstrap; Logistic; regression (search for similar items in EconPapers)
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(02)00397-8
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:61:y:2003:i:4:p:383-394

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().