New large-sample confidence intervals for a linear combination of binomial proportions

DOI10.1016/j.jspi.2007.07.008zbMath1131.62024OpenAlexW2038264699MaRDI QIDQ2480039

Scott A. Roths, Joshua M. Tebbs

Publication date: 28 March 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2007.07.008

zbMATH Keywords

nuisance parametersBayesian estimationreparameterizationmulticenter clinical trialGram-Schimdt othogonalization

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Parametric tolerance and confidence regions (62F25)

Related Items (8)

Optimal Method for Realizing Two-Sided Inferences About a Linear Combination of Two Proportions ⋮ Simultaneous inferences: new method of maximum combination ⋮ Approximate confidence intervals for a linear combination of binomial proportions: A new variant ⋮ New asymptotic inferences about the difference, ratio, and linear combination of two independent proportions ⋮ The optimal method to make inferences about a linear combination of proportions ⋮ A note on confidence interval estimation for a linear function of binomial proportions ⋮ Inferences about a linear combination of proportions ⋮ A comparison of two varying coefficient meta-analysis methods for an average risk difference

Cites Work

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• Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures
• Revisiting Beal's Confidence Intervals for the Difference of Two Binomial Proportions
• Asymptotic Confidence Intervals for the Difference between Two Binomial Parameters for Use with Small Samples
• Parametric Empirical Bayes Inference: Theory and Applications
• ON A METHOD OF ESTIMATING FREQUENCIES

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