int_part_vars_structure {dataquieR}R Documentation

Detect Expected Observations

Description

For each participant, check, if an observation was expected, given the PART_VARS from item-level metadata

Usage

int_part_vars_structure(
  label_col,
  study_data,
  item_level = "item_level",
  expected_observations = c("HIERARCHY", "SEGMENT"),
  disclose_problem_paprt_var_data = FALSE,
  meta_data = item_level,
  meta_data_v2
)

Arguments

label_col

character mapping attribute colnames(study_data) vs. meta_data[label_col]

study_data

study_data must have all relevant PART_VARS to avoid false-positives on PART_VARS missing from study_data

item_level

meta_data must be complete to avoid false positives on non-existing PART_VARS

expected_observations

enum HIERARCHY | SEGMENT. How should PART_VARS be handled: - SEGMENT: if PART_VAR is 1, an observation is expected - HIERARCHY: the default, if the PART_VAR is 1 for this variable and also for all PART_VARS of PART_VARS up in the hierarchy, an observation is expected.

disclose_problem_paprt_var_data

logical show the problematic data (PART_VAR only)

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.

Details

Descriptor

Value

empty list, so far – the function only warns.


[Package dataquieR version 2.5.1 Index]