Interval estimation for a binomial proportion: a bootstrap approach
(2008) In Journal of Statistical Computation and Simulation 78(12). p.1249-1263- Abstract
- This paper discusses the classic but still current problem of interval estimation of a binomial proportion. Bootstrap methods are presented for constructing such confidence intervals in a routine, automatic way. Three confidence intervals for a binomial proportion are compared and studied by means of a simulation study, namely: the Wald confidence interval, the Agresti-Coull interval and the bootstrap-t interval. A new confidence interval, the Agresti-Coull interval with bootstrap critical values, is also introduced and its good behaviour related to the average coverage probability is established by means of simulations.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1283896
- author
- Mantalos, Panagiotis LU and Zografos, Konstantinos
- organization
- publishing date
- 2008
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Coverage probability, Confidence intervals, Bootstrap, Agresti and Coull confidence interval, Binomial distribution
- in
- Journal of Statistical Computation and Simulation
- volume
- 78
- issue
- 12
- pages
- 1249 - 1263
- publisher
- Taylor & Francis
- external identifiers
-
- wos:000260497300010
- scopus:55249098177
- ISSN
- 1563-5163
- DOI
- 10.1080/00949650701749356
- language
- English
- LU publication?
- yes
- id
- fdac035e-6df5-4a04-8c3a-ee5695684e50 (old id 1283896)
- date added to LUP
- 2016-04-01 15:00:38
- date last changed
- 2022-01-28 03:37:36
@article{fdac035e-6df5-4a04-8c3a-ee5695684e50, abstract = {{This paper discusses the classic but still current problem of interval estimation of a binomial proportion. Bootstrap methods are presented for constructing such confidence intervals in a routine, automatic way. Three confidence intervals for a binomial proportion are compared and studied by means of a simulation study, namely: the Wald confidence interval, the Agresti-Coull interval and the bootstrap-t interval. A new confidence interval, the Agresti-Coull interval with bootstrap critical values, is also introduced and its good behaviour related to the average coverage probability is established by means of simulations.}}, author = {{Mantalos, Panagiotis and Zografos, Konstantinos}}, issn = {{1563-5163}}, keywords = {{Coverage probability; Confidence intervals; Bootstrap; Agresti and Coull confidence interval; Binomial distribution}}, language = {{eng}}, number = {{12}}, pages = {{1249--1263}}, publisher = {{Taylor & Francis}}, series = {{Journal of Statistical Computation and Simulation}}, title = {{Interval estimation for a binomial proportion: a bootstrap approach}}, url = {{http://dx.doi.org/10.1080/00949650701749356}}, doi = {{10.1080/00949650701749356}}, volume = {{78}}, year = {{2008}}, }