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Higher criticism is a multiple-comparison test concept arising from the situation where there are number of independent tests of significance and interest lies in the rejecting joint null hypothesis.
The fraction of the observed significances at the given α-level is compared to the expected fraction under the joint null and the difference between the two quantities is standardized and this standardized value then maximized over the range of significance levels to provide the higher criticism statistic. This statistic is efficient in assessing whether n normal means are all zero against the alternative that the small fraction is nonzero.
Quantalassay: The experiment in which the groups of subjects are exposed to the different doses of, generally, a drug, to which the particular number respond. Data from such type
Band matrix: A matrix which has its non zero elements arranged uniformly near to the diagonal, so that aij = 0 if (i - j)> ml or (j - i)> mu where aij are the elements of matrix a
The Null Hypothesis - H0: There is no autocorrelation The Alternative Hypothesis - H1: There is at least first order autocorrelation Rejection Criteria: Reject H0 if LBQ1 >
Length-biased sampling : The bias which arises in the sampling scheme based on the visits of patient, when some individuals are more likely to be chosen than others simply because
In an experiment, power is a function of 1. The number of variables being measured and the beta level 2. The effect size, internal validity and the beta level 3. The number of part
Battery reduction : A common term for reducing the number of variables of the interest in a study for the purposes of study and perhaps later data collection. For instance, an over
The generalization of the normal distribution used for the characterization of functions. It is known as a Gaussian process because it has Gaussian distributed finite dimensional m
A term commonly encountered in the application of the agglomerative hierarchical clustering techniques, where it refers to the 'tree-like' diagram illustrating the series of steps
The Null Hypothesis - H0: Model does not fit the data i.e. all slopes are equal to zero β 1 =β 2 =...=β k = 0 The Alternative Hypothesis - H1: Model does fit the data i.e. at
The function of a variable t which, when extended formally as a power series in t, yields factorial moments as the coefficients of the respective powers. If the P(t) is probability
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