int_unexp_records_segment: Check for unexpected data record count within segments

In dataquieR: Data Quality in Epidemiological Research

Check for unexpected data record count within segments

Description

This function contrasts the expected record number in each study segment in the metadata with the actual record number in each segment data frame.

Indicator

Usage

int_unexp_records_segment(
  study_segment,
  study_data,
  label_col,
  item_level = "item_level",
  data_record_count,
  meta_data = item_level,
  meta_data_segment = "segment_level",
  meta_data_v2,
  segment_level
)

Arguments

study_segment	character a character vector indicating the name of each study data frame, mandatory.
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
data_record_count	integer an integer vector with the number of expected data records, mandatory.
meta_data	data.frame old name for item_level
meta_data_segment	data.frame – optional: Segment level metadata
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.
segment_level	data.frame alias for meta_data_segment

Details

The current implementation does not take into account jump or missing codes, the function is rather based on checking whether NAs are present in the study data

Value

a list with

• SegmentData: data frame with the results of the quality check for unexpected data elements

• SegmentTable: data frame with selected unexpected data elements check results, used for the data quality report.

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