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Detecting Interaction Using a Two-way Multigroup Common Factor Model
authors Smeden, M. van
source Faculty of Social and Behavioural Theses (2011)
full text The full text of this item is not available.
document type Master thesis
disciplines Sociale Wetenschappen
abstract In this paper, a two-way multigroup common factor model (MG-CFM) is presented, which can be used to estimate two-way interaction between grouping variables on latent variables. By applying a likelihood ratio test, a two-way interaction can be tested. The effectiveness of this MG-CFM likelihood ratio test is evaluated in a Monte Carlo simulation, comparing statistical power and robustness to MANOVA’s F-test. The results of the simulation show that Type-I error control is satisfactory for both tests and considerable higher power can be achieved when a MG-CFM is used rather than a MANOVA.
keywords Factorial interaction, MG-CFA, MANOVA, latent means, likelihood ratio test, F-test, power, robustness.