create_IV: Calculate Information Value for a selected outcome variable

In wpa: Tools for Analysing and Visualising Viva Insights Data

Calculate Information Value for a selected outcome variable

Description

Specify an outcome variable and return IV outputs. All numeric variables in the dataset are used as predictor variables.

Usage

create_IV(
  data,
  predictors = NULL,
  outcome,
  bins = 5,
  siglevel = 0.05,
  exc_sig = FALSE,
  return = "plot"
)

Arguments

data	A Person Query dataset in the form of a data frame.
predictors	A character vector specifying the columns to be used as predictors. Defaults to NULL, where all numeric vectors in the data will be used as predictors.
outcome	A string specifying a binary variable, i.e. can only contain the values 1 or 0.
bins	Number of bins to use, defaults to 5.
siglevel	Significance level to use in comparing populations for the outcomes, defaults to 0.05
exc_sig	Logical value determining whether to exclude values where the p-value lies below what is set at siglevel. Defaults to FALSE, where p-value calculation does not happen altogether.
return	String specifying what to return. This must be one of the following strings: "plot" "summary" "list" "plot-WOE" "IV" See Value for more information.

Value

A different output is returned depending on the value passed to the return argument:

• "plot": 'ggplot' object. A bar plot showing the IV value of the top (maximum 12) variables.

• "summary": data frame. A summary table for the metric.

• "list": list. A list of outputs for all the input variables.

• "plot-WOE": A list of 'ggplot' objects that show the WOE for each predictor used in the model.

• "IV" returns a list object which mirrors the return in Information::create_infotables().

See Also

Other Variable Association: IV_by_period(), IV_report(), plot_WOE()

Other Information Value: IV_by_period(), IV_report(), plot_WOE()

Examples

# Return a summary table of IV
sq_data %>%
  dplyr::mutate(X = ifelse(Workweek_span > 40, 1, 0)) %>%
  create_IV(outcome = "X",
            predictors = c("Email_hours",
                           "Meeting_hours",
                           "Instant_Message_hours"),
            return = "plot")


# Return summary
sq_data %>%
  dplyr::mutate(X = ifelse(Collaboration_hours > 10, 1, 0)) %>%
  create_IV(outcome = "X",
            predictors = c("Email_hours", "Meeting_hours"),
            return = "summary")

wpa documentation built on Aug. 21, 2023, 5:11 p.m.