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Full-Text Articles in Social and Behavioral Sciences
The Effects Of Multicollinearity In Multilevel Models, Patrick Carl Clark Jr.
The Effects Of Multicollinearity In Multilevel Models, Patrick Carl Clark Jr.
Browse all Theses and Dissertations
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, …
Introduction To Data Science, Jeffrey M. Stanton
Introduction To Data Science, Jeffrey M. Stanton
School of Information Studies - Faculty Scholarship
In this Introduction to Data Science eBook, a series of data problems of increasing complexity is used to illustrate the skills and capabilities needed by data scientists. The open source data analysis program known as "R" and its graphical user interface companion "R-Studio" are used to work with real data examples to illustrate both the challenges of data science and some of the techniques used to address those challenges. To the greatest extent possible, real datasets reflecting important contemporary issues are used as the basis of the discussions.