int_part_vars_structure: Detect Expected Observations
In dataquieR: Data Quality in Epidemiological Research

int_part_vars_structure

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(
  study_data,
  meta_data,
  label_col = LABEL,
  expected_observations = c("HIERARCHY", "SEGMENT"),
  disclose_problem_paprt_var_data = FALSE
)

Arguments

`study_data`	study_data must have all relevant `PART_VARS` to avoid false-positives on `PART_VARS` missing from `study_data`
`meta_data`	meta_data must be complete to avoid false positives on non-existing `PART_VARS`
`label_col`	character mapping attribute `colnames(study_data)` vs. `meta_data[label_col]`
`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)