Testing multivariate mean collinearity via latent variable modelling.
A procedure for testing mean collinearity in multidimensional spaces is outlined, which is applicable in settings with missing data and can be used when examining group mean differences. The approach is based on non-linear parameter restrictions and is developed within the framework of latent variable modelling. The method provides useful information about the constellation of multiple response centroids in the populations studied, and is illustrated with an example.
Michigan State University, East Lansing, MI, USA. raykov@msu.edu
Tenko
T
Raykov
Spiridon
S
Penev
D001525:Behavioral Sciences / Q000706:statistics & numerical data*; D015982:Bias; D003198:Computer Simulation; D003625:Data Collection / Q000706:statistics & numerical data*; D006801:Humans; D008432:Mathematical Computing; D015233:Models, Statistical; D015999:Multivariate Analysis; D017711:Nonlinear Dynamics; D012984:Software