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The values assigned to factors for the individual sample units in a factor analysis. The most common approach is "regression method". When the factors are seen as the random variables this corresponds to the best linear unbiased predictor and if the factors are supposed to have normal distributions to the empirical Bayes prediction. The Bartlett technique is also sometimes used which corresponds to the max imum likelihood estimation of factor scores if the factors are seen as ?xed.
Unequal probability sampling is the sampling design in which the different sampling units in the population have different probabilities of being included in sample. The differing
Kendall's tau statistics : The measures of the correlation between the two sets of rankings. Kendall's tau itself (τ) is the rank correlation coefficient based on number of inversi
Ha: If hyperlipidemia is believed to be a side effect of second-generation antipsychotics (SGAs), then Hispanic patients with SGAs treatment will have the higher frequency of devel
Geographical information system (gis): The software and hardware configurations through which the digital georeferences are processed and displayed. Used to recognize the geograph
Chain-binomial models : Models arising in mathematical theory of the quite infectious diseases, which postulate that at any stage in the epidemic there are a certain number of the
Two-phase sampling is the sampling scheme including two distinct phases, in the first of which the information about the particular variables of interest is collected on all the m
Ignorability : The missing data mechanism is said to be ignorable for likelihood inference if (1) the joint likelihood for the responses of the interest and missing data indicators
Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig
Multidimensional scaling (MDS) is a generic term for a class of techniques or methods which attempt to construct a low-dimensional geometrical representation of the proximity matr
Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is
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