Model Building Clause Samples

Model Building. Prior to conducting the analysis, data were cleaned using an iterative three phase process of screening, diagnosing and editing (▇▇▇ ▇▇▇ ▇▇▇▇▇▇ et al., 2005). Screening involves using univariate and bivariate analyses and graphs to identify relationships among variables and “lack or excess of data, outliers, strange patterns in joint distributions and unexpected analysis results and other types of inferences and abstractions" (▇▇▇ ▇▇▇ ▇▇▇▇▇▇ et al., 2005; Wilkinson, 1999). Subsequently, we diagnosed potential issues (e.g., data is outside or inside the range of possible measurements) and treated the issues by correcting, deleting, or leaving the values and documented our choices. We also examined focal policies of interest for multicollinearity by calculating the Variance Inflation Factor (VIF). A VIF of 10 or greater was considered indicative of a potential issue suggesting that TANF policies should be examined in separate models. The VIF values ranged from 1-3.5, suggesting no such issue.