This function summarizes some properties of measurement variables.
util_dist_selection(study_data, val_lab = NULL)data frame with one row for each variable in the study data and the
following columns:
Variables contains the names of the variables
IsInteger contains a check whether the variable contains integer values
only (variables coded as factor will be converted to integers)
IsMultCat contains a check for variables with integer or string values
whether there are more than two categories
NCategory contains the number of distinct values for variables with
values coded as integers or strings (excluding NA and
empty entries)
AnyNegative contains a check whether the variable contains any negative
values
NDistinct contains the number of distinct values
PropZeroes reports the proportion of zeroes
study data, pre-processed with prep_prepare_dataframes
to replace missing value codes by NA
matching metadata column containing the VALUE_LABELS
as vector (if available)
Other metadata_management:
CAN_THIS_BE_REMOVED_util_combine_missing_lists(),
util_find_free_missing_code(),
util_find_var_by_meta(),
util_get_var_att_names_of_level(),
util_get_vars_in_segment(),
util_looks_like_missing(),
util_no_value_labels(),
util_validate_known_meta(),
util_validate_missing_lists()