Introduction to the Problem

The given problem involves creating a function that calculates conditional probabilities for athletes in a dataset based on their hair color and other characteristics. The initial function provided takes specific variables and levels of these variables as inputs, but it does not allow for the calculation of conditional probabilities.

Approach to Solving the Problem

To solve this problem, we need to create a more flexible function that can take any number of input variables, their respective levels, and a variable for which the conditional probability should be calculated. This new function will use the prop.table function from R to calculate the desired probabilities.

Modified Function

my_function <- function(dataset, var1 = NULL, var2 = NULL, var3 = NULL, var4 = NULL,
                        conditional_var = NULL) {
  
  # Create a logical vector to store the rows that match the specified criteria
  selection <- rep(TRUE, nrow(dataset))
  
  # Filter rows based on the specified levels of input variables
  if (!is.null(var1)) {
    selection <- selection & dataset[, var1] %in% var1
  }
  
  if (!is.null(var2)) {
    selection <- selection & dataset[, var2] %in% var2
  }
  
  if (!is.null(var3)) {
    selection <- selection & dataset[, var3] %in% var3
  }
  
  if (!is.null(var4)) {
    selection <- selection & dataset[, var4] %in% var4
  }
  
  # Select the rows that match the specified criteria
  selected_rows <- dataset[selection, ]
  
  # Return the selected rows with conditional probabilities
  if (is.null(conditional_var)) {
    return(selected_rows) 
  } else {
    probabilities <- prop.table(table(selected_rows[conditional_var]), useNA = "ifany")
    
    # Check if all variables in the input have values for the given variable
    for (var in c(var1, var2, var3, var4)) {
      if (!exists(var) | sum(is.na(selected_rows[, var])) > 0) {
        stop(paste0("Variable '", var, "' does not contain all required values for the conditional probability"))
      }
    }
    
    return(probabilities)
  }
}

# Example usage:
my_function(dataset, var1 = c("black", "brown"), var3 = c("football"), conditional_var = c("var2"))

Explanation of the Modified Function

The modified function my_function takes an optional vector dataset, along with four input variables (var1, var2, var3, var4) and one variable for which the conditional probability should be calculated (conditional_var).

• If all input variables are specified, it filters the dataset based on these conditions.
• It then calculates the probabilities of each level of conditional_var using prop.table.
• To ensure that all required variables exist for the given variable and contain values, we added a check at the end.

Usage

To use this modified function, simply call it with your dataset and desired input parameters. If you want to calculate conditional probabilities for multiple variables, provide them in the same way as before.

Last modified on 2024-02-10