Non-parametric inference for balanced randomization designs

DOI10.1016/j.jspi.2006.06.020zbMath1104.62055OpenAlexW1982933249MaRDI QIDQ866642

Andrew. L. Rukhin

Publication date: 14 February 2007

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.2006.06.020

zbMATH Keywords

probability generating functionpermutation testsclinical trialsload balancingselection biasmultinomial trialsnormal order statisticsaccidental biasStirling's numbers

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) Order statistics; empirical distribution functions (62G30)

Related Items (1)

Stopping Rules in Balanced Allocation Problems: Exact and Asymptotic Distributions

Cites Work

• K-treatment comparisons with restricted randomization rules in clinical trials
• The analysis of sequential experiments with feedback to subjects
• A note on Blackwell and Hodges (1957) and Diaconis and Graham (1981)
• Asymptotic inference with response-adaptive treatment allocation designs
• Limiting Distributions in Sequential Occupancy Problem
• Design for the Control of Selection Bias
• Significance tests with restricted randomization design
• Efron's conjecture on vulnerability to bias in a method for balancing sequential trials
• On the random allocation design for the control of selection bias in sequential experiments
• Bias properties and nonparametric inference for truncated binomial randomization
• The use of random allocation for the control of selection bias
• Forcing a sequential experiment to be balanced
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