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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, …