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Regression dilution is the term which is applied when a covariate in the model cannot be measured directly and instead of that a related observed value must be used in analysis. In common, if the model is correctly specified in the terms of the 'true' covariate, then an equivalent form of the model with a easy error structure will not hold for observed values. In such type of cases, ignoring the measured values will lead to the biased estimates of the parameters in the model. It is often also referred to as the errors in variables problem.
Classification matrix: A term many times used in discriminant analysis for the matrix summarizing the results and outputs obtained from the derived classi?cation rule, and obtaine
Multitrait multi method model (MTMM) is the form of confirmatory factor analysis model in which the different techniques of measurement are used to measure each of the latent vari
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Ordination is the procedure of reducing the dimensionality (that is the number of variables) of multivariate data by deriving the small number of new variables which contain much
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Influence statistics: The range of statistics designed to assess the effect or the in?uence of an observation in determining results of the regression analysis. The general approa
Response feature analysis is the approach to the analysis of longitudinal data including the calculation of the suitable summary measures from the set of repeated measures on each
Negative binomial distribution is the probability distribution of number of failures, X, before the kth success in the sequence of Bernoulli trials where the probability of succes
Nuisance parameter : The parameter of the model in which there is no scienti?c interest but whose values are generally required (but in usual are unknown) to make inferences about
Hamilton County judges try thousands of cases per year. In an overwhelming majority of the cases disposed, the verdict stands as rendered. However, some cases are appeale
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