Interval Estimation for a Binomial Proportion

By Lawrence D. Brown, Tommaso Cai, Anirban Dasgupta. 2001

3,589 citations recorded by the source corpus.

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Citations in the corpus

Self-Refine: Iterative Refinement with Self-Feedback (2023, background): “Table 13 shows results from Table 1 with Wilson confidence interval (Brown et al., 2001) (at α= 99% confidence interval) and statistical significance.”
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs (2017, methodology): “To compute the one-sided confidence interval we used the Wilson method ((Brown et al., 2001)) which gives a lower bound”
YAGO3: A Knowledge Base from Multilingual Wikipedias (2015, methodology): “Here, we opt for the Wilson Score Interval [7], because it is particularly well-suited for small samples.”
A significance test of interaction in 2 x K designs with proportions (2007, positive): “This equation is extracted from the equation of the Wilson confidence interval of proportions (Newcombe & Altman, 2000; Brown et al., 2001):”
Confidence intervals for two sample binomial distribution (2005, methodology): “Coverage Probabilty -0.4 -0.2 0.0 0.2 0.4 0.88 0.90 0.92 0.94 0.96 0 .98 ) performs very well in constructing the CI of p, even when p is close to 0 or 1 (see Brown et al., 2001).”
Attributing Effects to a Cluster-Randomized Get-Out-the-Vote Campaign (2009, methodology): “Proviso (a) addresses L1, whereas provisos (b) and (c) address L2, by heading off known shortcomings of Wald-type variance approximations with small samples (Zheng and Little 2005, section 4; Elliott 2009, section 4.1) and with binary data (Brown, Cai, and DasGupta 2001).”
Can Evidence Impact Attitudes? Public Reactions to Evidence of Gender Bias in STEM Fields (2015, methodology): “, statistically greater than zero) of responses (Brown et al., 2001; Cox & Hinkley, 1974).”
PAC Confidence Predictions for Deep Neural Network Classifiers (2020, methodology): “The following expression is equivalent due to the relationship between the Binomial and Beta distributions (Brown et al., 2001): Now, for each of the K bins, we apply ˆΘ CP with conﬁdence level α = — i.e., where Here, W k is the set of observations of successes vs. failures corresponding to the…”
Inference for functions of parameters in discrete distributions based on fiducial approach: Binomial and Poisson cases (2010, result): “On the basis of the coverage studies by Brown et al. (2001), the fiducial test should be comparable with the score test.”
Fuzzy and randomized confidence intervals and P-values (2005, background): “A recent article (Brown, Cai, and DasGupta, 2001) reviews crisp confidence intervals for binomial models.”