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.

Usage

int_unexp_records_segment(
  study_segment,
  data_record_count,
  study_data,
  meta_data
)

Arguments

study_segment	character a character vector indicating the name of each study data frame, mandatory.
data_record_count	integer an integer vector with the number of expected data records, mandatory.
study_data	data.frame the data frame that contains the measurements, mandatory.
meta_data	data.frame the data frame that contains metadata attributes of the study data, mandatory.

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.

Examples

## Not run: 
study_data <- readRDS(system.file("extdata", "ship.RDS", package = "dataquieR"))
meta_data <- readRDS(system.file("extdata", "ship_meta.RDS", package = "dataquieR"))

int_unexp_records_segment(
  study_segment = c("PART_STUDY", "PART_INTERVIEW"),
  data_record_count = c(3000, 1100),
  study_data = study_data,
  meta_data = meta_data
)

## End(Not run)

dataquieR documentation built on July 26, 2023, 6:10 p.m.