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Confidence with confidence intervals
Indian Journal of Ophthalmology, 1997 When considering the results of a study that reports one treatment to be better than another, what the practicing ophthalmologist really wants to know is the magnitude of the difference between treatment groups. If this difference is large enough, we may
Thomas Ravi +3 more
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The Effect of the Outliers and Leverage Points in the Construction of the Bayesian and Bootstrap Confidence Intervals [PDF]
المجلة العراقية للعلوم الاحصائية, 2019 The aim of this research is to compare the bootstrap confidence intervals with the Bayesian confidence intervals for smoothing splines as well as the traditional confidence intervals to determine which of these limits are best in the presence of Outliers
Muzahim Mohammed
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Confidence intervals and other statistical intervals in metrology [PDF]
International Journal of Metrology and Quality Engineering, 2012 Typically, a measurement is regarded as being incomplete without a statement of uncertainty being provided with the result. Usually, the corresponding interval of measurement uncertainty will be an evaluated confidence interval, assuming that the ...
Willink R.
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Confidence Intervals for Variance Components [PDF]
The Egyptian Statistical Journal, 1982 In the previous paper Estimation of Variance Components in the One-Way Random Effects Model (ESJ Vol. 25, No. 2, pp. 1-11), several methods for constructing confidence inte-rvals for the components of variance were presented. In the present paper we will
Oskar Feichtinger, Keh-Ming Husueh
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Confidence intervals for fMRI activation maps. [PDF]
PLoS ONE, 2013 Neuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location.
Stephen A Engel, Philip C Burton
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Confidence Intervals for Seroprevalence
Statistical Science, 2022 This paper concerns the construction of confidence intervals in standard seroprevalence surveys. In particular, we discuss methods for constructing confidence intervals for the proportion of individuals in a population infected with a disease using a sample of antibody test results and measurements of the test's false positive and false negative rates.
DiCiccio, Thomas J. +3 more
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Confidence Intervals for Stochastic Arithmetic [PDF]
ACM Transactions on Mathematical Software, 2021 Quantifying errors and losses due to the use of Floating-point (FP) calculations in industrial scientific computing codes is an important part of the Verification, Validation, and Uncertainty Quantification process. Stochastic Arithmetic is one way to model and estimate FP losses of accuracy, which scales well to large, industrial codes.
Sohier, Devan +5 more
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Confidence Intervals of COVID-19 Vaccine Efficacy Rates
Numeracy, 2021 This tutorial uses publicly available data from drug makers and the Food and Drug Administration to guide learners to estimate the confidence intervals of COVID-19 vaccine efficacy rates with a Bayesian framework.
Frank Wang
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Generalized Confidence Intervals for Zero-Inflated Pareto Distribution
Mathematics, 2021 This paper considers interval estimations for the mean of Pareto distribution with excess zeros. Three approaches for interval estimation are proposed based on fiducial generalized pivotal quantities (FGPQs), respectively.
Xiao Wang, Xinmin Li
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Multivariate Confidence Intervals [PDF]
, 2017 Confidence intervals are a popular way to visualize and analyze data distributions. Unlike p-values, they can convey information both about statistical significance as well as effect size. However, very little work exists on applying confidence intervals to multivariate data.
Korpela, Jussi +4 more
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