A quadratic bootstrap method and improved estimation in logistic regression
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.
Year of publication: |
2003
|
---|---|
Authors: | Claeskens, Gerda ; Aerts, Marc ; Molenberghs, Geert |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 61.2003, 4, p. 383-394
|
Publisher: |
Elsevier |
Keywords: | Bias correction Bootstrap confidence interval One-step bootstrap Logistic regression |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
A Tutorial on the Practical Use and Implication of Complete Sufficient Statistics
Hermans, Lisa, (2018)
-
A flexible method to measure synchrony in neuronal firing
Faes, Christel, (2008)
-
Graduate Education in Statistics and Data Science : The Why, When, Where, Who, and What
Aerts, Marc, (2021)
- More ...