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Direct linkMorse, Brendan J.; Johanson, George A.; Griffeth, Rodger W. – Applied Psychological Measurement, 2012
Recent simulation research has demonstrated that using simple raw score to operationalize a latent construct can result in inflated Type I error rates for the interaction term of a moderated statistical model when the interaction (or lack thereof) is proposed at the latent variable level. Rescaling the scores using an appropriate item response…
Descriptors: Item Response Theory, Multiple Regression Analysis, Error of Measurement, Models
Peer reviewedMcFatter, Robert M. – Applied Psychological Measurement, 1979
The usual interpretation of suppressor effects in a multiple regression equation assumes that the correlations among variables have been generated by a particular structural model. How such a regression equation is interpreted is shown to be dependent on the structural model deemed appropriate. (Author/JKS)
Descriptors: Correlation, Critical Path Method, Data Analysis, Models
