Results 241 to 250 of about 20,682 (267)

The power of Efron's biased coin design

Journal of Statistical Planning and Inference, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Tests Conditional on Imbalance with Biased Coin Designs.

1986
Abstract : Distributional properties of the treatment assignment variables T sub 1, ..., T sub n under Efron's (1971) biased coin design are derived. These properties are conditional on the terminal imbalance of the treatment allocation. Recursive procedures are presented for obtaining the conditional moments of T sub 1, ..., T sub n.
Edsel Pena, Myles Hollander
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An optimal response adaptive biased coin design with k heteroscedastic treatments

Journal of Statistical Planning and Inference, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gwise, Thomas E., Zhou, Jianhui, Hu, Feifang   +2 more
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Dose Finding Using the Biased Coin Up‐and‐Down Design and Isotonic Regression

Biometrics, 2002
Summary.We are interested in finding a dose that has a prespecified toxicity rate in the target population. In this article, we investigate five estimators of the target dose to be used with the up‐and‐down biased coin design (BCD) Introduced By Durham and Flournoy (1994,Statistical Decision Theory and Related Topics).These estimators are derived using
Stylianou, Mario, Flournoy, Nancy
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Covariate-adjusted inference for doubly adaptive biased coin design

Statistical Methods in Medical Research
Randomized controlled trials (RCTs) are pivotal for evaluating the efficacy of medical treatments and interventions, serving as a cornerstone in clinical research. In addition to randomization, achieving balances among multiple targets, such as statistical validity, efficiency, and ethical considerations, is also a central issue in RCTs.
Fuyi Tu, Wei Ma
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On inferences from Wei's biased coin design for clinical trials

Biometrika, 1990
Wei (1988) analyzed data from a clinical trial in which an urn-sampling model was used to allocate patients to treatments. The trial resulted in 11 patients being allocated to the experimental treatment, all successes, and with one patient allocated to the control treatment, a failure.
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An adaptive biased coin design for the behrens-fisher problem

Sequential Analysis, 1990
Wei(1978) introduced the adaptive biased coin design to reduce experimenter bias and offer a compromise between perfect balance and complete randomization. In situations such as the Behrens-Fisher problem, balance is not necessarily desired and the optimal ratio of sample sizes is unknown.
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A two-dimensional biased coin design for dual-agent dose-finding trials

Clinical Trials, 2015
Background: Given the limited efficacy observed with single agents, there is growing interest in Phase I clinical trial designs that allow for identification of the maximum tolerated combination of two agents.
Zhichao, Sun, Thomas M, Braun
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The adaptive accelerated biased coin design for phase I clinical trials

Journal of Applied Statistics, 2011
Phase I clinical trials are designed to study several doses of the same drug in a small group of patients to determine the maximum tolerated dose (MTD), which is defined as the dose that is associated with dose-limiting toxicity (DLT) in a desired fraction Γ of patients.
Nan Jia, Thomas M. Braun
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Sequential Monitoring of Conditional Randomization Tests: Generalized Biased Coin Designs

Sequential Analysis, 2008
Abstract For the generalized biased coin class of randomization procedures, Smythe (1988) proved asymptotic normality of the conditional linear rank test. Clinical trialists often undertake interim analysis to determine whether to stop the trial early for a substantial treatment effect.
Yanqiong Zhang, William F. Rosenberger
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