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Testing multivariate mean collinearity via latent variable modelling
Author(s) -
Raykov Tenko,
Penev Spiridon
Publication year - 2010
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1348/000711009x471901
Subject(s) - collinearity , latent variable , multivariate statistics , latent variable model , statistics , mathematics , centroid , variable (mathematics) , missing data , computer science , econometrics , artificial intelligence , mathematical analysis
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.