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The Effects Of Multicollinearity In Multilevel Models, Patrick Carl Clark Jr.
The Effects Of Multicollinearity In Multilevel Models, Patrick Carl Clark Jr.
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This study examined a method for calculating the impact of multicollinearity on multilevel modeling. The major research questions concerned a) how the simulation design factors affect (multilevel variance inflation factor) MVIF, b) how MVIF affects standard errors of regression coefficients, and c) how MVIF affects significance of regression coefficients. Monte Carlo simulations were conducted to address these questions. Predictor relationships were manipulated in order to simulate multicollinearity. Findings indicate that a) increases in relationships among Level 1 predictors and also relationships among Level 2 predictors led to increased MVIF for those specific variables, b) as MVIF increases for a predictor, …
Systems Factorial Technology With R, Joseph W. Houpt, Leslie M. Blaha, John P. Mcintire, Paul R. Havig, James T. Townsend
Systems Factorial Technology With R, Joseph W. Houpt, Leslie M. Blaha, John P. Mcintire, Paul R. Havig, James T. Townsend
Joseph W. Houpt
Systems Factorial Technology (SFT) comprises a set of powerful nonparametric models and measures, together with a theory-driven experiment methodology termed the Double Factorial Paradigm (DFP), for assessing the cognitive information processing mechanisms supporting the processing of multiple sources of information in a given task. We provide an overview of the model-based measures of SFT together with a tutorial on designing a DFP experiment to take advantage of all SFT measures in a single experiment. Illustrative examples are given to highlight the breadth of applicability of these techniques across psychology. We further introduce and demonstrate a new package for performing SFT …