Function provides summary statistics for individual categorical predictors

Source: R/fn_exp_categorical.R

Provides bivariate summary statistics for all the categorical predictors against target variables. Output includes chi - square value, degrees of freedom, information value, p-value

ExpStat(X, Y, valueOfGood = NULL)

Arguments

X

Independent categorical variable.
Y

Binary response variable, it can take values of either 1 or 0.
valueOfGood

Value of Y that is used as reference category.

Value

The function provides summary statistics like

  • Unique number of levels

  • Chi square statistics

  • P value

  • df Degrees of freedom

  • IV Information value

  • Predictive class

Details

Summary statistics included Pearson's Chi-squared Test for Count Data, "chisq.test" which performs chi-squared contingency table tests and goodness-of-fit tests. If any NA value present in X or Y variable, which will be considered as NA as in category while computing the contingency table.

Also added unique levels for each X categorical variables and degrees of freedom

See also

chisq.test

Examples

X = mtcars$carb
Y = mtcars$am
ExpStat(X,Y,valueOfGood = 1)

#>      X-squared            
#> [1,] "6"                  
#> [2,] "6.237"              
#> [3,] "0.284"              
#> [4,] "5"                  
#> [5,] "0.17"               
#> [6,] "0.44"               
#> [7,] "Strong"             
#> [8,] "Somewhat Predictive"