datascreen: Data Screening for Regression

In doomlab/MeMoBootR: Mediation-Moderation with Bootstrapping in R

Data Screening for Regression

Description

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.

Usage

datascreen(eq, df, with_out = T)

Arguments

eq	The full equation with all x, m, and cvs created from the createformula() function.
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 TRUE or exclude them from the data screening FALSE.

Examples

datascreen(eq = "mpg ~ cyl + disp + drat + gear",
           df = mtcars, with_out = TRUE)

doomlab/MeMoBootR documentation built on April 5, 2023, 8:27 p.m.