Description Usage Arguments Examples
This function using the data screening procedures outlined by Tabachnick and Fidell (2012) to analyze the data for outliers using Mahalanobis distance, Cook's, and Leverage values. Further, the output includes correlations for additivity/multicollinearity, and plots for linearity, normality, and homogeneity/homoscedasticity. You can learn more about the data screening procedure implemented here at the Statistics of DOOM YouTube channel.
1 | datascreen(eq, df, with_out = T)
|
eq |
The full equation with all x, m, and cvs created from the
|
df |
The dataframe where the columns from the formula can be found. Note that only the columns used in the analysis will be screened. |
with_out |
A logical value where you want to keep the outliers in
the data screening |
1 2 | datascreen(eq = "mpg ~ cyl + disp + drat + gear",
df = mtcars, with_out = TRUE)
|
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