Bias properties and nonparametric inference for truncated binomial randomization

DOI10.1080/10485250310001604604zbMath1054.62137OpenAlexW2000336147MaRDI QIDQ4470124

William F. Rosenberger, Andrew. L. Rukhin

Publication date: 22 June 2004

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485250310001604604

zbMATH Keywords

Permutation testAsymptotic normalityAccidental biasSelection biasLinear rank testRandom allocation rule

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (6)

Non-parametric inference for balanced randomization designs ⋮ On asymptotic normality of certain linear rank statistics ⋮ On asymptotic normality of the randomization-based logrank test ⋮ Randomization with non-uniform allocations: fulfillment time distributions and bias properties ⋮ On linear rank tests for truncated binomial randomization ⋮ The weighted log-rank class under truncated binomial design: saddlepoint \(p\)-values and confidence intervals

Cites Work

• K-treatment comparisons with restricted randomization rules in clinical trials
• Conditional inference for restricted randomization designs
• Asymptotic inference with response-adaptive treatment allocation designs
• Design for the Control of Selection Bias
• Significance tests with restricted randomization design
• On the random allocation design for the control of selection bias in sequential experiments
• The use of random allocation for the control of selection bias
• Forcing a sequential experiment to be balanced
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