New asymptotic inferences about the difference, ratio, and linear combination of two independent proportions

DOI10.1080/03610918.2015.1005231zbMath1362.62042OpenAlexW2550090052MaRDI QIDQ2974957

A. Martín Andrés, M. Álvarez Hernández

Publication date: 11 April 2017

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2015.1005231

zbMATH Keywords

likelihood ratio testrelative riskdifference between proportionsarc-sine transformationlinear combination of two proportions

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Point estimation (62F10)

Related Items (2)

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Cites Work

• Two-tailed approximate confidence intervals for the ratio of proportions
• An improved confidence interval for a linear function of binomial proportions
• A note on confidence interval estimation for a linear function of binomial proportions
• Small-sample comparisons of confidence intervals for the difference of two independent binomial proportions
• Choosing the optimal unconditioned test for comparing two independent proportions
• On the validity condition of the chi-squared test in \(2 \times 2\) tables
• New large-sample confidence intervals for a linear combination of binomial proportions
• On Small-Sample Confidence Intervals for Parameters in Discrete Distributions
• Asymptotic two-tailed confidence intervals for the difference of proportions
• Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures
• Simultaneous Confidence Intervals for Comparing Binomial Parameters
• Comparing Two Diagnostic Tests against the Same "Gold Standard" in the Same Sample
• The optimal method to make inferences about a linear combination of proportions
• Inferences about a linear combination of proportions
• Optimal Method for Realizing Two-Sided Inferences About a Linear Combination of Two Proportions
• Maximum Average-Power (MAP) Tests
• Dealing with discreteness: making `exact’ confidence intervals for proportions, differences of proportions, and odds ratios more exact

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