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The Shortest Clopper–Pearson Randomized Confidence Interval for Binomial Probability
Revstat Statistical Journal, 2017 Zieli´nski (2010) showed the existence of the shortest Clopper–Pearson confidence interval for binomial probability. The method of obtaining such an interval was presented as well. Unfortunately, the confidence interval obtained has one disadvantage: it
Wojciech Zieliński
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Generating confidence intervals on biological networks
BMC Bioinformatics, 2007 Background In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interacting nodes. The structure of the network may introduce dependencies among the
Stumpf Michael PH, Thorne Thomas
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A note on confidence intervals for deblurred images [PDF]
Opuscula Mathematica, 2020 We consider pointwise asymptotic confidence intervals for images that are blurred and observed in additive white noise. This amounts to solving a stochastic inverse problem with a convolution operator.
Michał Biel, Zbigniew Szkutnik
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Calculating confidence intervals for impact numbers
BMC Medical Research Methodology, 2006 Background Standard effect measures such as risk difference and attributable risk are frequently used in epidemiological studies and public health research to describe the effect of exposures.
Bender Ralf +3 more
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Correlation-adjusted standard errors and confidence intervals for within-subject designs: A simple multiplicative approach [PDF]
Tutorials in Quantitative Methods for Psychology, 2019 In within-subject designs, the multiple scores of a given participant are correlated. This correlation implies that the observed variance can be partitioned into between-subject variance and between-measure variance.
Cousineau, Denis
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Using the confidence interval confidently [PDF]
Journal of Thoracic Disease, 2017 Biomedical research is seldom done with entire populations but rather with samples drawn from a population. Although we work with samples, our goal is to describe and draw inferences regarding the underlying population. It is possible to use a sample statistic and estimates of error in the sample to get a fair idea of the population parameter, not as a
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Simple and Honest Confidence Intervals in Nonparametric Regression [PDF]
Quantitative Economics, 2016 We consider the problem of constructing honest confidence intervals (CIs) for a scalar parameter of interest, such as the regression discontinuity parameter, in nonparametric regression based on kernel or local polynomial estimators.
Timothy B. Armstrong, M. Kolesár
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Calculating unreported confidence intervals for paired data
BMC Medical Research Methodology, 2011 Background Confidence intervals (or associated standard errors) facilitate assessment of the practical importance of the findings of a health study, and their incorporation into a meta-analysis.
Fagerland Morten W, Hirji Karim F
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An extension of within-subject confidence intervals to models with crossed random effects [PDF]
Tutorials in Quantitative Methods for Psychology, 2017 A common problem in displaying within-subject data is that of how to show confidence intervals that accurately reflect the pattern of significant differences between conditions. The Cousineau-Morey method \parencite {c05,m08} is a widely used solution to
Politzer-Ahles, Stephen
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Confidence Intervals: From tests of statistical significance to confidence intervals, range hypotheses and substantial effects [PDF]
Tutorials in Quantitative Methods for Psychology, 2006 For the last 50 years of research in quantitative social sciences, the empirical evaluation of scientific hypotheses has been based on the rejection or not of the null hypothesis.
Dominic Beaulieu-Prévost
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