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In this article, we consider the efficiency of three experimental designs for comparing two treatments with correlated binary outcomes.
Efficient crossover designs for comparing t test treatments to one control treatment with three periods is considered.
We study the optimality, efficiency, and robustness of crossover designs for comparing several test treatments to a control treatment.
The randomized complete block designs, RCBDs, are among the most popular of block designs for comparing a set of experimental treatments.
A method is given for determining optimal designs for comparing treatments in blocks when the units within blocks are linearly ordered and a polynomial trend influences the response.
E-optimal designs for comparing three treatments in blocks of size three are identified, where intrablock observations are correlated according to a first order autoregressive error process with parameter ρ∈ 0,1).
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There are numerous comparison protocols designed for comparing encrypted values [15, 16, 18].
The test is consistent against generic nonlinear alternatives, and is designed for comparing nested models.
In addition, such measurement is designed for comparing two markets rather than a single market only as in the case of China here.
The study was designed for comparing the efficacy and cost effectiveness of Pregabalin and Duloxetine used in Diabetic Neuropathic Pain.
In addition, a discrete-time PID control scheme for PUMA robot is designed for comparing energy consumption of OTGA with algorithms developed by previous authors.
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