Better Confidence Intervals for a Binomial Proportion
Communications, 2010 Interval estimation of a binomial proportion is one of the basic problems in statistics. In technical practice a binomial proportion is often used in statistical quality control.
Ivana Pobocikova
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Improved Confidence Intervals for the Youden Index. [PDF]
PLoS ONE, 2015 The Youden Index is a summary measurement of the receiver operating characteristic (ROC) curve for the accuracy of a diagnostic test with ordinal or continuous endpoints.
Guogen Shan
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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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Significant results: statistical or clinical? [PDF]
Korean Journal of Anesthesiology, 2016 The null hypothesis significance test method is popular in biological and medical research. Many researchers have used this method for their research without exact knowledge, though it has both merits and shortcomings. Readers will know its shortcomings,
Sangil Park
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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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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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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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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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