des_summary: Compute Descriptive Statistics

In dataquieR: Data Quality in Epidemiological Research

Compute Descriptive Statistics

Description

generates a descriptive overview of the variables in resp_vars.

Descriptor

Usage

des_summary(
  resp_vars = NULL,
  study_data,
  label_col,
  item_level = "item_level",
  meta_data = item_level,
  meta_data_v2,
  hard_limits_removal = getOption("dataquieR.des_summary_hard_lim_remove",
    dataquieR.des_summary_hard_lim_remove_default),
  ...
)

Arguments

resp_vars	variable the name of the measurement variables
study_data	data.frame the data frame that contains the measurements
label_col	variable attribute the name of the column in the metadata with labels of variables
item_level	data.frame the data frame that contains metadata attributes of study data
meta_data	data.frame old name for item_level
meta_data_v2	character path to workbook like metadata file, see prep_load_workbook_like_file for details. ALL LOADED DATAFRAMES WILL BE PURGED, using prep_purge_data_frame_cache, if you specify meta_data_v2.
hard_limits_removal	logical if TRUE values outside hard limits are removed from the data before calculating descriptive statistics. The default is FALSE
...	arguments to be passed to all called indicator functions if applicable.

Details

TODO

Value

a list with:

• SummaryTable: data.frame

• SummaryData: data.frame

See Also

Online Documentation

Examples

## Not run: 
xx <- des_summary(study_data = "study_data", meta_data_v2 = "meta_data_v2")
xx$SummaryData

## End(Not run)

dataquieR documentation built on Jan. 8, 2026, 5:08 p.m.