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Randomized consent design is the design at first introduced to overcome some of the perceived ethical problems facing clinicians entering patients in the clinical trials including random allotment. After the patient's eligibility is established the patient is randomized to one of the two treatments A and B. Patients randomized to the treatment A are approached for patient consent. The patients are asked if they are willing to receive the therapy A for their illness. All the potential risks, benefits and treatment options are discussed. If patient agrees for it, treatment A is given. If the patient does not agree, the patient receives treatment B or some other alternative treatment. Those patients who are randomly assigned to group B are similarly asked about the treatment B, and transferred to the alternative treatment if consent is not provided.
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The Expectation/Conditional Maximization Either algorithm which is the generalization of ECM algorithm attained by replacing some of the CM-steps of ECM which maximize the constrai
Graphical deception : Statistical graphics which are not as honest as they should be. It is relatively simple. To mislead the unwary with the graphical material. For instance, c
MAZ experiments : The Mixture-amount experiments which include control tests for which the entire amount of the mixture is set to zero. Examples comprise drugs (some patients do no
Briefly explain the importance of forecasting for managers?
Locally weighted regression is the method of regression analysis in which the polynomials of degree one (linear) or two (quadratic) are used to approximate regression function in
Hot deck is a method broadly used in surveys for imputing the missing values. In its easiest form the method includes sampling with replacement m values from the sample respondent
Bioinformatics : Essentially the application of the information theory to biology to deal with the deluge of the information resulting from the advances in molecular biology. The m
Uncertainty analysis is the process for assessing the variability in the outcome variable that is due to the uncertainty in estimating the values of input parameters. A sensitivit
ain why the simulated result doesn''t have to be exact as the theoretical calculation
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