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Internet-based language production research with overt articulation: Proof of concept, challenges, and practical advice
Language production experiments with overt articulation have thus far only scarcely been conducted online, mostly due to technical difficulties...
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Quantifying social asymmetric structures
Many social phenomena involve a set of dyadic relations among agents whose actions may be dependent. Although individualistic approaches have...
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Four simultaneous component models for the analysis of multivariate time series from more than one subject to model intraindividual and interindividual differences
A class of four simultaneous component models for the exploratory analysis of multivariate time series collected from more than one subject...
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Continuous time state space modeling of panel data by means of sem
Maximum likelihood parameter estimation of the continuous time linear stochastic state space model is considered on the basis of large N discrete time...
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Improved Standard Errors of Standardized Parameters in Covariance Structure Models: Implications for Construct Explication
Because measurement scales of observed variables in social and behavioral sciences are often arbitrary, and because the sample correlation matrix,...
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Weighted least squares fitting using ordinary least squares algorithms
A general approach for fitting a model to a data matrix by weighted least squares (WLS) is studied. This approach consists of iteratively performing...
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An inequality between the weighted average and the rowwise correlation coefficient for proximity matrices
De Vries (1993) discusses Pearson's product-moment correlation, Spearman's rank correlation, and Kendall's rank-correlation coefficient for assessing...
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The rowwise correlation between two proximity matrices and the partial rowwise correlation
This paper discusses rowwise matrix correlation, based on the weighted sum of correlations between all pairs of corresponding rows of two proximity...
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Principal component analysis with external information on both subjects and variables
A method for structural analysis of multivariate data is proposed that combines features of regression analysis and principal component analysis. In...