util_no_value_labels: Select really numeric variables

In dataquieR: Data Quality in Epidemiological Research

Select really numeric variables

Description

Reduce resp_vars to those, which are either float or integer without VALUE_LABELS, i.e. likely numeric but not a factor

Usage

util_no_value_labels(resp_vars, meta_data, label_col, warn = TRUE, stop = TRUE)

Arguments

resp_vars	variable list len=1-2. the name of the continuous measurement variable
meta_data	data.frame the data frame that contains metadata attributes of study data
label_col	variable attribute the name of the column in the metadata with labels of variables
warn	logical warn about removed variable names
stop	logical stop on no matching resp_var

Value

character vector of matching resp_vars.

See Also

Other metadata_management: CAN_THIS_BE_REMOVED_util_combine_missing_lists(), util_dist_selection(), 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_validate_known_meta(), util_validate_missing_lists()

dataquieR documentation built on May 29, 2024, 7:18 a.m.