Analysis of conditional covariance structure models
This paper presents a statistical development for analyzing covariance structure models with certain variables held constant. The theory enables one to assess partial correlations among variables. Models are defined based on the conditional covariance matrices, and they are studied by the maximum likelihood approach with the appropriate conditional sample covariance matrices. It is shown that existing computer package programs and statistical methods can be easily applied to analyze the new models. Examples from two real data sets are reported to illustrate the theory.
scientific article; zbMATH DE number 3945120
scientific article