Another look at confidence intervals: Proposal for a more relevant and transparent approach
Creators
- 1. Department of Physics, University of Oxford, Oxford OX1 3RH (United Kingdom)
- 2. Department of Physics and Astronomy, University of British Columbia, Vancouver V6T 1Z1 (Canada)
Description
The behaviors of various confidence/credible interval constructions are explored, particularly in the region of low event numbers where methods diverge most. We highlight a number of challenges, such as the treatment of nuisance parameters, and common misconceptions associated with such constructions. An informal survey of the literature suggests that confidence intervals are not always defined in relevant ways and are too often misinterpreted and/or misapplied. This can lead to seemingly paradoxical behaviors and flawed comparisons regarding the relevance of experimental results. We therefore conclude that there is a need for a more pragmatic strategy which recognizes that, while it is critical to objectively convey the information content of the data, there is also a strong desire to derive bounds on model parameter values and a natural instinct to interpret things this way. Accordingly, we attempt to put aside philosophical biases in favor of a practical view to propose a more transparent and self-consistent approach that better addresses these issues
Availability note (English)
Available from http://dx.doi.org/10.1016/j.nima.2014.11.081Additional details
Identifiers
- DOI
- 10.1016/j.nima.2014.11.081;
- arXiv
- arXiv:1405.5010v2;
- PII
- S0168-9002(14)01395-3;
Publishing Information
- Journal Title
- Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment
- Journal Volume
- 774
- Journal Page Range
- p. 103-119
- ISSN
- 0168-9002
- CODEN
- NIMAER
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 46125556
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING;
- Descriptors DEI
- COMPARATIVE EVALUATIONS; DATA; DATA ANALYSIS; MATHEMATICAL MODELS; MEASURING METHODS; PROBABILITY; PROPOSALS; STATISTICS; VALIDATION; VERIFICATION
- Descriptors DEC
- DATA PROCESSING; EVALUATION; INFORMATION; MATHEMATICS; PROCESSING; TESTING
Optional Information
- Copyright
- Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.