Confidence intervals for robust estimates of measurement uncertainty Article Swipe
Peter D. Rostron
,
Tom Fearn
,
Michael H. Ramsey
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1007/s00769-019-01417-4
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1007/s00769-019-01417-4
Uncertainties arising at different stages of a measurement process can be estimated using analysis of variance (ANOVA) on duplicated measurements. In some cases, it is also desirable to calculate confidence intervals for these uncertainties. This can be achieved using probability models that assume the measurement data are normally distributed. However, it is often the case in practice that a set of otherwise normally distributed measurement values is contaminated by a small number of outlying values, which may have a disproportionate effect on the variances calculated using the ‘classical’ form of ANOVA. In this case, robust ANOVA methods are able to provide variance estimates that are much closer to the parameters of the underlying normal distributions. A method using bootstrapping to calculate confidence intervals from robust estimates of variances is proposed and evaluated and is shown to work well when the number of outlying values is small. The method has been implemented in a visual basic program.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s00769-019-01417-4
- https://link.springer.com/content/pdf/10.1007/s00769-019-01417-4.pdf
- OA Status
- hybrid
- Cited By
- 20
- References
- 14
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2994928544
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- OpenAlex ID
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https://openalex.org/W2994928544Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s00769-019-01417-4Digital Object Identifier
- Title
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Confidence intervals for robust estimates of measurement uncertaintyWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-02-04Full publication date if available
- Authors
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Peter D. Rostron, Tom Fearn, Michael H. RamseyList of authors in order
- Landing page
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https://doi.org/10.1007/s00769-019-01417-4Publisher landing page
- PDF URL
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https://link.springer.com/content/pdf/10.1007/s00769-019-01417-4.pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://link.springer.com/content/pdf/10.1007/s00769-019-01417-4.pdfDirect OA link when available
- Concepts
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Bootstrapping (finance), Statistics, Confidence interval, Variance (accounting), Mathematics, Robust confidence intervals, Measurement uncertainty, Analysis of variance, Observational error, Variance components, Econometrics, Accounting, BusinessTop concepts (fields/topics) attached by OpenAlex
- Cited by
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20Total citation count in OpenAlex
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2025: 2, 2024: 6, 2023: 4, 2022: 5, 2021: 3Per-year citation counts (last 5 years)
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14Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.also | 26 |
| abstract_inverted_index.been | 150 |
| abstract_inverted_index.case | 55 |
| abstract_inverted_index.data | 46 |
| abstract_inverted_index.form | 89 |
| abstract_inverted_index.from | 124 |
| abstract_inverted_index.have | 78 |
| abstract_inverted_index.much | 106 |
| abstract_inverted_index.some | 22 |
| abstract_inverted_index.that | 42, 58, 104 |
| abstract_inverted_index.this | 93 |
| abstract_inverted_index.well | 138 |
| abstract_inverted_index.when | 139 |
| abstract_inverted_index.work | 137 |
| abstract_inverted_index.ANOVA | 96 |
| abstract_inverted_index.basic | 155 |
| abstract_inverted_index.case, | 94 |
| abstract_inverted_index.often | 53 |
| abstract_inverted_index.shown | 135 |
| abstract_inverted_index.small | 71 |
| abstract_inverted_index.these | 33 |
| abstract_inverted_index.using | 13, 39, 86, 118 |
| abstract_inverted_index.which | 76 |
| abstract_inverted_index.ANOVA. | 91 |
| abstract_inverted_index.assume | 43 |
| abstract_inverted_index.cases, | 23 |
| abstract_inverted_index.closer | 107 |
| abstract_inverted_index.effect | 81 |
| abstract_inverted_index.method | 117, 148 |
| abstract_inverted_index.models | 41 |
| abstract_inverted_index.normal | 114 |
| abstract_inverted_index.number | 72, 141 |
| abstract_inverted_index.robust | 95, 125 |
| abstract_inverted_index.small. | 146 |
| abstract_inverted_index.stages | 5 |
| abstract_inverted_index.values | 66, 144 |
| abstract_inverted_index.visual | 154 |
| abstract_inverted_index.(ANOVA) | 17 |
| abstract_inverted_index.arising | 2 |
| abstract_inverted_index.methods | 97 |
| abstract_inverted_index.process | 9 |
| abstract_inverted_index.provide | 101 |
| abstract_inverted_index.values, | 75 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.However, | 50 |
| abstract_inverted_index.achieved | 38 |
| abstract_inverted_index.analysis | 14 |
| abstract_inverted_index.normally | 48, 63 |
| abstract_inverted_index.outlying | 74, 143 |
| abstract_inverted_index.practice | 57 |
| abstract_inverted_index.program. | 156 |
| abstract_inverted_index.proposed | 130 |
| abstract_inverted_index.variance | 16, 102 |
| abstract_inverted_index.calculate | 29, 121 |
| abstract_inverted_index.desirable | 27 |
| abstract_inverted_index.different | 4 |
| abstract_inverted_index.estimated | 12 |
| abstract_inverted_index.estimates | 103, 126 |
| abstract_inverted_index.evaluated | 132 |
| abstract_inverted_index.intervals | 31, 123 |
| abstract_inverted_index.otherwise | 62 |
| abstract_inverted_index.variances | 84, 128 |
| abstract_inverted_index.calculated | 85 |
| abstract_inverted_index.confidence | 30, 122 |
| abstract_inverted_index.duplicated | 19 |
| abstract_inverted_index.parameters | 110 |
| abstract_inverted_index.underlying | 113 |
| abstract_inverted_index.distributed | 64 |
| abstract_inverted_index.implemented | 151 |
| abstract_inverted_index.measurement | 8, 45, 65 |
| abstract_inverted_index.probability | 40 |
| abstract_inverted_index.contaminated | 68 |
| abstract_inverted_index.distributed. | 49 |
| abstract_inverted_index.Uncertainties | 1 |
| abstract_inverted_index.bootstrapping | 119 |
| abstract_inverted_index.measurements. | 20 |
| abstract_inverted_index.distributions. | 115 |
| abstract_inverted_index.uncertainties. | 34 |
| abstract_inverted_index.‘classical’ | 88 |
| abstract_inverted_index.disproportionate | 80 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 95 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.882263 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |