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Multi dimensional unfolding is the form of multidimensional scaling applicable to both the rectangular proximity matrices where the rows and columns refer to the different sets of stimuli, for instance, judges and soft drinks, and asymmetric proximity matrices, for instance, citations of journal A by journal B and vice versa. Unfolding was introduced as a manner of representing judges and stimuli on a single straight line so that the rank-order of the stimuli as determined by each of the judge is reflected by the rank order of the distance of stimuli to that judge.
O'Brien's two-sample tests are the extensions of the conventional tests for assessing the differences between treatment groups which take account of the possible heterogeneous nat
Correlation matrix : A square, symmetric matrix with the rows and columns corresponding to the variables, in which the non diagonal elements are correlations between the pairs of t
Matching is the method of making a study group and a comparison group comparable with respect to the extraneous factors. Generally used in the retrospective studies when selecting
The method or technique for producing the sequence of parameter estimates that, under the mild regularity conditions, converges to maximum likelihood estimator. Of particular signi
Population averaged models are the models for kind of clustered data in which the marginal expectation of response variable is the main focus of interest. An alternative approach
An approach to investigations designed to recognize a particular medical condition in the large population, usually by means of a blood test, which might result in the considerable
The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
Huffman code is used to compress data file, where the data is represented as a sequence of characters. Huffman's greedy algorithm uses a table giving how often each character occur
Thomas Economic Forecasting, Inc. and Harmon Econometrics have the same mean error in forecasting the stock market over the last ten years. However, the standard deviation for Thom
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