Relevant bibliographies by topics / Confidence intervals

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Confidence intervals'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Confidence intervals"

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Perry, D. C., X. L. Griffin, M. Dritsaki, M. L. Costa, and N. Parsons. "Becoming confident about confidence intervals." Bone & Joint Journal 99-B, no. 5 (2017): 563–65. http://dx.doi.org/10.1302/0301-620x.99b5.bjj-2017-0075.

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Kahraman, Cengiz, Basar Oztaysi, and Sezi Cevik Onar. "Interval-Valued Intuitionistic Fuzzy Confidence Intervals." Journal of Intelligent Systems 28, no. 2 (2019): 307–19. http://dx.doi.org/10.1515/jisys-2017-0139.

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Abstract Confidence intervals are useful tools for statistical decision-making purposes. In case of incomplete and vague data, fuzzy confidence intervals can be used for decision making under uncertainty. In this paper, we develop interval-valued intuitionistic fuzzy (IVIF) confidence intervals for population mean, population proportion, differences in means of two populations, and differences in proportions of two populations. The developed IVIF intervals can be used in cases of both finite and infinite population sizes. The developed fuzzy confidence intervals are equivalent decision-making
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Darling, HS. "Are you confident about your confidence in confidence intervals?" Cancer Research, Statistics, and Treatment 5, no. 1 (2022): 139. http://dx.doi.org/10.4103/crst.crst_75_22.

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Columb, M. O., and H. E. Thomson. "Confidence with confidence intervals." British Journal of Anaesthesia 95, no. 1 (2005): 111–12. http://dx.doi.org/10.1093/bja/aei569.

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El-Masri, Maher M. "Confidence in confidence intervals!" Canadian Journal of Nursing Research 49, no. 1 (2017): 3–4. http://dx.doi.org/10.1177/0844562117692406.

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Tufanaru, Catalin. "Confidence in confidence intervals." JBI Database of Systematic Reviews and Implementation Reports 14, no. 5 (2016): 1–2. http://dx.doi.org/10.11124/jbisrir-2016-002923.

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Gordon, Ian. "Confidence intervals." Medical Journal of Australia 145, no. 7 (1986): 361–62. http://dx.doi.org/10.5694/j.1326-5377.1986.tb113858.x.

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BROWNER, WARREN S. "Confidence Intervals." Annals of Internal Medicine 105, no. 6 (1986): 973. http://dx.doi.org/10.7326/0003-4819-105-6-973_3.

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Twa, Michael D. "Confidence Intervals." Optometry and Vision Science 97, no. 5 (2020): 315. http://dx.doi.org/10.1097/opx.0000000000001527.

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Campbell, Malcolm. "Confidence intervals." African Journal of Midwifery and Women's Health 10, no. 3 (2016): 115–19. http://dx.doi.org/10.12968/ajmw.2016.10.3.115.

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Dissertations / Theses on the topic "Confidence intervals"

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Turner, Heather Jean. "A Performance Evaluation of Confidence Intervals for Ordinal Coefficient Alpha." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc801899/.

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Ordinal coefficient alpha is a newly derived non-parametric reliability estimate. As with any point estimate, ordinal coefficient alpha is merely an estimate of a population parameter and tends to vary from sample to sample. Researchers report the confidence interval to provide readers with the amount of precision obtained. Several methods with differing computational approaches exist for confidence interval estimation for alpha, including the Fisher, Feldt, Bonner, and Hakstian and Whalen (HW) techniques. Overall, coverage rates for the various methods were unacceptably low with the Fisher me
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Karch, Angela Irene. "Confidence intervals in life-testing." Virtual Press, 1986. http://liblink.bsu.edu/uhtbin/catkey/458972.

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The purpose of the study was to develop a sequential test method for obtaining a confidence interval in life-testing. The problem of using a maximum likelihood estimator based upon grouped data was considered. Life-times that were investigated are described by the exponential distribution. The sequential test used the length of the confidence interval as a stopping rule.The test method and necessary calculations were described. The results of using different length values as a stopping rule were compared using a computer simulation. Results are indicated in two categories: percent of time the
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Yu, Zhuqing, and 俞翥清. "Uniformly consistent bootstrap confidence intervals." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B47752993.

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The bootstrap methods are widely used for constructing confidence intervals. However, the conventional bootstrap fails to be consistent under some nonstandard circumstances. The m out of n bootstrap is usually adopted to restore consistency, provided that a correct convergence rate can be specified for the plug-in estimators. In this thesis, we re-investigate the asymptotic properties of the bootstrap in a moving-parameter framework in which the underlying distribution is allowed to depend on n. We consider the problem of setting uniformly consistent confidence intervals for two non-re
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Huang, Ching-ying Maghsoodloo Saeed. "Comparing the overlapping of two independent confidence intervals with a single confidence interval for two normal population parameters." Auburn, Ala, 2008. http://hdl.handle.net/10415/1480.

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Sak, Halis, Wolfgang Hörmann, and Josef Leydold. "Better Confidence Intervals for Importance Sampling." WU Vienna University of Economics and Business, 2010. http://epub.wu.ac.at/3017/1/techreport%2D106.pdf.

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It is well known that for highly skewed distributions the standard method of using the t statistic for the confidence interval of the mean does not give robust results. This is an important problem for importance sampling (IS) as its final distribution is often skewed due to a heavy tailed weight distribution. In this paper, we first explain Hall's transformation and its variants to correct the confidence interval of the mean and then evaluate the performance of these methods for two numerical examples from finance which have closed-form solutions. Finally, we assess the performance of these m
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Erlank, Warrick. "Constructing confidence intervals for polarization mode dispersion." Thesis, Nelson Mandela Metropolitan University, 2008. http://hdl.handle.net/10948/951.

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Polarization mode dispersion (PMD) causes significant impairment in high bit-rate optical telecommunications systems. Knowledge of a fibre’s PMD mean value, and the relevant confidence interval, is essential for determining a fibre’s maximum allowable bit-rate. Various methods of confidence interval construction for time series data were tested in this dissertation using simulation. These included the autocovariance-matrix methods as suggested by Box and Jenkins, as well as the more practical and simpler batch means methods. Some of these methods were shown to be significantly better than the
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De, La Riva Torres Omar. "Empirical likelihood confidence intervals for survey data." Thesis, University of Southampton, 2014. https://eprints.soton.ac.uk/374699/.

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Nandeshwar, Ashutosh R. "Models for calculating confidence intervals for neural networks." Morgantown, W. Va. : [West Virginia University Libraries], 2006. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4600.

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Thesis (M.S.)--West Virginia University, 2006.<br>Title from document title page. Document formatted into pages; contains x, 65 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 62-65).
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Hansson, Patrik. "A naïve sampling model of intuitive confidence intervals." Doctoral thesis, Umeå University, Psychology, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1354.

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<p>A particular field in research on judgment and decision making (JDM) is concerned with realism of confidence in one’s knowledge. An interesting finding is the so-called format dependence effect, which implies that assessment of the same probability distribution generates different conclusions about over- or underconfidence depending on the assessment format. In particular, expressing a belief about some unknown continuous quantity (e.g., a stock value) in the form of an intuitive confidence interval is severely prone to overconfidence as compared to expressing the belief as an assessment of
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Hansson, Patrik. "A naïve sampling model of intuitive confidence intervals /." Umeå : Department of Psychology, Umeå University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1354.

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Books on the topic "Confidence intervals"

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Smithson, Michael. Confidence Intervals. SAGE Publications, Inc., 2003. http://dx.doi.org/10.4135/9781412983761.

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A, Graybill Franklin, ed. Confidence intervals on variance components. M. Dekker, 1992.

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J, Gardner M., and Altman Douglas G, eds. Statistics with confidence: Confidence intervals and statistical guidelines. British Medical Journal, 1989.

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DiCiccio, Thomas J. Bootstrap confidence intervals and bootstrap approximation. University of Toronto, Dept. of Statistics, 1985.

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Siegmund, David. Sequential analysis: Tests and confidence intervals. Springer-Verlag, 1985.

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Siegmund, David. Sequential analysis: Tests and confidence intervals. Springer-Verlag, 2010.

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DiCiccio, Thomas J. On the implementation of profile likelihood methods. University of Toronto, Dept. of Statistics, 1991.

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Lawrence, Michael J. "Factors affecting judgemental forecasts and confidence intervals". INSEAD, 1986.

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Chan, Y. M. Robustness of Fieller's theorem and comparison with bootstrap method. University of Toronto, Dept. of Statistics, 1985.

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Tibshirani, Robert. Variance stabilization and the bootstrap. University of Toronto, Dept. of Statistics, 1987.

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Book chapters on the topic "Confidence intervals"

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Mudelsee, Manfred. "Bootstrap Confidence Intervals Confidence interval,Bootstrap." In Atmospheric and Oceanographic Sciences Library. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04450-7_3.

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Foster, Dean P., Robert A. Stine, and Richard P. Waterman. "Confidence Intervals." In Basic Business Statistics. Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4612-1696-4_5.

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Lista, Luca. "Confidence Intervals." In Statistical Methods for Data Analysis in Particle Physics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62840-0_7.

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Foster, Dean P., Robert A. Stine, and Richard P. Waterman. "Confidence Intervals." In Basic Business Statistics. Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4757-2717-3_5.

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Wiley, Matt, and Joshua F. Wiley. "Confidence Intervals." In Beginning R 4. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6053-1_9.

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Lista, Luca. "Confidence Intervals." In Statistical Methods for Data Analysis in Particle Physics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-20176-4_6.

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Gillard, Jonathan. "Confidence Intervals." In Springer Undergraduate Mathematics Series. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39561-2_4.

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Kiefer, Jack Carl. "Confidence Intervals." In Introduction to Statistical Inference. Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4613-9578-2_9.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Confidence Intervals." In Statistical Analysis of Clinical Data on a Pocket Calculator. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1211-9_5.

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Andersen, Erling B., Niels-Erik Jensen, and Nils Kousgaard. "Confidence Intervals." In Statistics for Economics, Business Administration, and the Social Sciences. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-95528-0_11.

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Conference papers on the topic "Confidence intervals"

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Zheng, Julia, Yuya Nishida, Elizabeth A. C. Heath-Heckman, and Kevin J. Liu. "Estimating confidence intervals on reconstructed cophylogenies using bootstrap resampling." In 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024. https://doi.org/10.1109/bibm62325.2024.10821822.

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Ludlow, Jed, and T. D. Williamson. "Statistical Tolerance Intervals: A Better Approach to In-Line Inspection Performance Assessment." In CORROSION 2012. NACE International, 2012. https://doi.org/10.5006/c2012-01312.

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Abstract The requirement to validate the performance of in-line inspection (ILI) is outlined in the API 1163 standard. Appendix E of that standard is primarily focused on using statistical hypothesis tests on field validation measurements. An initial focus on hypothesis testing masks the more important pipeline integrity question at hand: Based upon the field validation measurements obtained, what is a defensible estimate of the uncertainty in this set of ILI measurements? The general theory of statistical tolerance intervals provides a framework for developing these uncertainty estimates and
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Sharifnia, Ensieh, and Simon H. Tindemans. "Reliable Confidence Intervals for Monte Carlo-Based Resource Adequacy Studies." In 2024 International Conference on Smart Energy Systems and Technologies (SEST). IEEE, 2024. http://dx.doi.org/10.1109/sest61601.2024.10694674.

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Malinowski, Roman, Emmanuelle Sarrazin, Emmanuel Dubois, Loïc Dumas, and Sébastien Destercke. "Robust Confidence Intervals for Digital Surface Models Using Satellite Photogrammetry." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642890.

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Guo, Yameng, and Seppe vanden Broucke. "Learning from Uncertainty: Improving Churn Prediction using Conformal Confidence Intervals." In 2024 International Conference on Machine Learning and Applications (ICMLA). IEEE, 2024. https://doi.org/10.1109/icmla61862.2024.00008.

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Weber, Thomas A. "Relatively Robust Economic Order Quantity with Optimal Laplacian Confidence Intervals." In 2025 International Research Conference on Smart Computing and Systems Engineering (SCSE). IEEE, 2025. https://doi.org/10.1109/scse65633.2025.11030973.

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Prosper, Harrison B. "Confidence Intervals." In INSTRUMENTATION IN ELEMENTARY PARTICLE PHYSICS. AIP, 2003. http://dx.doi.org/10.1063/1.1604076.

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Kaplan, Jennifer, and Kristen Roland. "Confidence Means What?!?: Lexical Ambiguity in the Interpretation of Confidence Intervals." In Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. International Association for Statistical Education, 2022. http://dx.doi.org/10.52041/iase.icots11.t8h2.

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Associations of Statistics and Psychology recommend reporting interval estimates, such as confidence intervals, when communicating data-based results. Previous research in statistics education, however, has identified the word confidence as having lexical ambiguity for students learning statistics. This study investigates the nature of this ambiguity with the interpretation of confidence intervals. Analysis of transcripts from task-based interviews revealed four themes, (a) sureness/belief, (b) confident in outcome, (c) confusion of chance/probability, and (d) equivalence of chance/probability
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Samuelson, Frank W., and Robert F. Wagner. "Bootstrapped MRMC confidence intervals." In Medical Imaging, edited by Miguel P. Eckstein and Yulei Jiang. SPIE, 2005. http://dx.doi.org/10.1117/12.597660.

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Aguirre, Janete F. R., and Frederico R. B. Cruz. "REVISITING JACKKNIFE CONFIDENCE INTERVALS." In SIMPóSIO BRASILEIRO DE PESQUISA OPERACIONAL. Galoa, 2022. https://doi.org/10.59254/sbpo-2022-157347.

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Reports on the topic "Confidence intervals"

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Romer, David. In Praise of Confidence Intervals. National Bureau of Economic Research, 2020. http://dx.doi.org/10.3386/w26672.

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Hjort, Nils L. Bayesian Nonparametric Bootstrap Confidence Intervals. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada161786.

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Lu, Zhan-Qian John. Estimating Instrument Performance: with Confidence Intervals and Confidence Bounds. National Institute of Standards and Technology, 2020. http://dx.doi.org/10.6028/nist.tn.2119.

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Carlin, Bradley P., and Alan E. Gelfand. Approaches for Empirical Bayes Confidence Intervals. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada205775.

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Weigend, Andreas S., and David A. Nix. Predictions with Confidence Intervals (Local Error Bars). Defense Technical Information Center, 1994. http://dx.doi.org/10.21236/ada451363.

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Stanny, R. R. Iterated-Bootstrap Confidence Intervals for the Mean. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada279802.

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Bukin, A. A Comparison of Methods for Confidence Intervals. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/826815.

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Donaldson, J. R., and R. B. Schnabel. Computational Experience with Confidence Regions and Confidence Intervals for Nonlinear Least Squares. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada158456.

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Younes, W., A. Ratkiewicz, and J. J. Ressler. Confidence Intervals from Realizations of Simulated Nuclear Data. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1399727.

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Verbeke, J. Estimation of Confidence Intervals for Multiplication and Efficiency. Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/964524.

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