The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Statistical Data Analysis in the Computer Age
Abstract
Most of our familiar statistical methods, such as hypothesis testing, linear regression, analysis of variance, and maximum likelihood estimation, were designed to be implemented on mechanical calculators. Modern electronic computation has encouraged a host of new statistical methods that require fewer distributional assumptions than their predecessors and can be applied to more complicated statistical estimators. These methods allow the scientist to explore and describe data and draw valid statistical inferences without the usual concerns for mathematical tractability. This is possible because traditional methods of mathematical analysis are replaced by specially constructed computer algorithms. Mathematics has not disappeared from statistical theory. It is the main method for deciding which algorithms are correct and efficient tools for automating statistical inference.
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“A bootstrap method analogous to a 2-tailed paired t-test was used to assess pre- to post-intervention changes, as some datasets were too small to reasonably verify normality”
From Multi-family pediatric pain group therapy: Capturing acceptance and cultivating change (2017) · cites this paper as [33]
Citations
Cites
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Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,867
Robust Locally Weighted Regression and Smoothing Scatterplots
Cleveland, W. S. (1979) · Journal of the American Statistical Association · doi:10.1080/01621459.1979.10481038 · Cited by 11,594
Brown, R. A., Hastie, T. J., & Tibshirani, R. J. (1991) · Biometrics · doi:10.2307/2532174 · Cited by 8,263
Self-citationEfron, B., & Tibshirani, R. (1986) · Statistical Science · doi:10.1214/ss/1177013815 · Cited by 6,033
Self-citationRobust Statistics: The Approach Based on Influence Functions
Ruppert, D. (1987) · Technometrics · doi:10.2307/1269782 · Cited by 3,880
Why Isn't Everyone a Bayesian?
Efron, B. (1986) · The American Statistician · doi:10.1080/00031305.1986.10475342 · Cited by 379
Self-citationA review of bootstrap confidence intervals
Diciccio, T. J., & Romano, J. P. (1988) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1988.tb01732.x · Cited by 314
Compliance as an Explanatory Variable in Clinical Trials
Efron, B., & Feldman, D. (1991) · Journal of the American Statistical Association · doi:10.1080/01621459.1991.10474996 · Cited by 307
Self-citationHINKLEY, D. V. (1988) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1988.tb01731.x · Cited by 215
Computer-Intensive Methods in Statistical Regression
Efron, B. (1988) · SIAM Review · doi:10.1137/1030093 · Cited by 48
Self-citationPredicting chemically induced duodenal ulcer and adrenal necrosis with classification trees.
Giampaolo, C., Gray, A. T., Olshen, R. A., & Szabó, S. (1991) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.88.14.6298 · Cited by 22
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Research works printed but not linked: 5
- EFRON, B, STAT SCI 1: 54 (1986).
- Giampaolo, C., Proceedings of the National Academy of Sciences of the United States of America 88: 6298 (1991).
- Hampel, F. R., Robust Statistics: TheApproach Based on Influence Functions: 29 (1986).
- Huber, P., Robust Statistics: 5 (1981).
- Williams, W. G., Journal of Thoracic and Cardiovascular Surgery 10: 222 (1991).
Cited by
Sorted by citations
Free R value: a novel statistical quantity for assessing the accuracy of crystal structures
Brünger, A. T. (1992) · Nature · doi:10.1038/355472a0 · Cited by 3,877
Hastie, T. J., & Tibshirani, R. J. (2014) · Wiley StatsRef: Statistics Reference Online · doi:10.1002/9781118445112.stat03141 · Cited by 3,156
Self-citation(2004) · New England Journal of Medicine · doi:10.1056/nejmoa032193 · Cited by 2,565
Primary forests are irreplaceable for sustaining tropical biodiversity
Gibson, L., Lee, T. M., Koh, L. P., Brook, B. W., Gardner, T. A., Barlow, J., Peres, C. A., Bradshaw, C. J. A., Laurance, W. F., Lovejoy, T. E., et al. (2011) · Nature · doi:10.1038/nature10425 · Cited by 2,147
Generalized additive models for medical research
Hastie, T. J., & Tibshirani, R. J. (1995) · Statistical Methods in Medical Research · doi:10.1177/096228029500400302 · Cited by 1,275
Self-citation
Metadata
- Authors
- Efron, B., & Tibshirani, R.
- Affiliations
- Stanford University (US)
- University of Toronto (CA)
- ORCID
- Tibshirani, Robert
- Venue
- Science
- Published
- 1991-07-26
- Volume
- 253
- Issue
- 5018
- Pages
- 390-395
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2045925085
- Cited by
- 1,192
- References
- 11
- Citations by year
- 2026: 14 · 2025: 24 · 2024: 34 · 2023: 24 · 2022: 30 · 2021: 29 · 2020: 39 · 2019: 24 · 2018: 35 · 2017: 44 · 2016: 25 · 2015: 30 · 2014: 28 · 2013: 43 · 2012: 48
- FWCI
- 49.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- statistical inference, hypothesis testing, linear regression, analysis of variance, maximum likelihood estimation, distributional assumptions, statistical software, statistical computing
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