add_to_dictionary       Add an element to the data dictionary
add_to_report           Add an element to the report object
check_date_sequence     Checks whether the order in a sequence of date
                        events is chronological. order.
check_subject_ids       Check whether the subject IDs comply with the
                        expected format. When incorrect IDs are found,
                        the function sends a warning and the user can
                        call the 'correct_subject_ids' function to
                        correct them.
clean_data              Clean and standardize data
clean_using_dictionary
                        Perform dictionary-based cleaning
common_na_strings       Common strings representing missing values
convert_numeric_to_date
                        Convert numeric to date
convert_to_numeric      Convert columns into numeric
correct_subject_ids     Correct the wrong subject IDs based on the
                        user-provided values.
find_duplicates         Identify and return duplicated rows in a data
                        frame or linelist.
get_default_params      Set and return 'clean_data' default parameters
print_report            Generate report from data cleaning operations
remove_constants        Remove constant data, including empty rows,
                        empty columns, and columns with constant
                        values.
remove_duplicates       Remove duplicates
replace_missing_values
                        Replace missing values with 'NA'
scan_data               Scan through a data frame and return the
                        proportion of 'missing', 'numeric', 'Date',
                        'character', 'logical' values.
standardize_column_names
                        Standardize column names of a data frame or
                        line list
standardize_dates       Standardize date variables
timespan                Calculate time span between dates
