int_all_datastructure_segment {dataquieR}R Documentation

Wrapper function to check for segment data structure

Description

This function tests for unexpected elements and records, as well as duplicated identifiers and content. The unexpected element record check can be conducted by providing the number of expected records or an additional table with the expected records. It is possible to conduct the checks by study segments or to consider only selected segments.

Indicator

Usage

int_all_datastructure_segment(
  study_data,
  label_col,
  item_level = "item_level",
  meta_data = item_level,
  meta_data_v2,
  segment_level,
  meta_data_segment = "segment_level"
)

Arguments

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.

segment_level

data.frame alias for meta_data_segment

meta_data_segment

data.frame the data frame that contains the metadata for the segment level, mandatory

Value

a list with

Examples

## Not run: 
out_segment <- int_all_datastructure_segment(
  meta_data_segment = "meta_data_segment",
  study_data = "ship",
  meta_data = "ship_meta"
)

study_data <- cars
meta_data <- dataquieR::prep_create_meta(VAR_NAMES = c("speedx", "distx"),
  DATA_TYPE = c("integer", "integer"), MISSING_LIST = "|", JUMP_LIST = "|",
  STUDY_SEGMENT = c("Intro", "Ex"))

out_segment <- int_all_datastructure_segment(
  meta_data_segment = "meta_data_segment",
  study_data = study_data,
  meta_data = meta_data
)

## End(Not run)

[Package dataquieR version 2.5.1 Index]