Scandinavian Journal of Statistics, Vol. 43, No. 4 (December 2016), pp. 1035-1045 (11 pages) Linear structural equation models, which relate random variables via linear inter-dependencies and Gaussian ...
Although the methodology for handling ordinal and dichotomous observed variables in structural equation models (SEMs) is developing rapidly, several important issues are unresolved. One of these is ...
Genome-wide expression and protein profiles provide powerful tools for large-scale analyses of gene interaction and identification of pathways underlying cells' response to perturbations. Clustering ...
Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance ...
Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance ...
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