Handle missing values according to a specified strategy

Provides a centralized mechanism for dealing with missing values in heteroscedasticity tests. The function can either drop incomplete cases, emit warnings, or fail fast when missingness is not permitted.

Usage

rhandleMissingValues(data, variables, strategy = "complete_cases")

Arguments

data

A data.frame containing the data to be processed.

variables

Character vector of variable names to inspect for missing values.

strategy

Strategy describing how missing values should be handled. The options are:

• "complete_cases" – remove incomplete rows and emit a warning that summarizes the data loss.

• "warn" – behaves identically to "complete_cases" but is provided as a semantic alias when a calling test wants to emphasize the warning behaviour explicitly.

• "fail" – abort when any missing values are detected.

Value

A list with components data (the processed data frame), removed_cases (row indices removed), removed_count (number of removed observations), removed_fraction (proportion removed relative to the original data), removed_variables (variables with observed missingness), and loss_message (the formatted warning text).