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Steinley, Douglas – Psychometrika, 2007
Given that a minor condition holds (e.g., the number of variables is greater than the number of clusters), a nontrivial lower bound for the sum-of-squares error criterion in K-means clustering is derived. By calculating the lower bound for several different situations, a method is developed to determine the adequacy of cluster solution based on…
Descriptors: Multivariate Analysis, Least Squares Statistics, Error of Measurement, Psychometrics
Maydeu-Olivares, Albert – Psychometrika, 2006
Discretized multivariate normal structural models are often estimated using multistage estimation procedures. The asymptotic properties of parameter estimates, standard errors, and tests of structural restrictions on thresholds and polychoric correlations are well known. It was not clear how to assess the overall discrepancy between the…
Descriptors: Structural Equation Models, Multivariate Analysis, Correlation, Error of Measurement

Longford, Nicholas T. – Psychometrika, 1997
It is demonstrated that, in the presence of population information, a linear combination of true scores can be estimated more efficiently than by the same linear combination of the observed scores. Three criteria for optimality are discussed, but they yield the same solution, described as a multivariate shrinkage estimator. (Author/SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Multivariate Analysis, Population Distribution

Huynh, Huynh – Psychometrika, 1982
A Bayesian framework for making mastery/nonmastery decisions based on multivariate test data is described. Overall, mastery is granted if the posterion expected loss associated with such action is smaller than the one incurred by denying mastery. (Author/JKS)
Descriptors: Bayesian Statistics, Criterion Referenced Tests, Cutting Scores, Error of Measurement