int_part_vars_structure

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

Data quality assessments guided by a
'data quality framework introduced by Schmidt and colleagues, 2021'
<doi:10.1186/s12874-021-01252-7> target the
data quality dimensions integrity, completeness, consistency, and
accuracy. The scope of applicable functions rests on the
availability of extensive metadata which can be provided in
spreadsheet tables. Either standardized (e.g. as 'html5' reports) or
individually tailored reports can be generated. For an introduction
into the specification of corresponding metadata, please refer to the
'package website'
<https://dataquality.qihs.uni-greifswald.de/Annotation_of_Metadata.html>.

Stephan Struckmann

dataquieR

Data Quality in Epidemiological Research

University Medicine Greifswald 

Elisa Kasbohm

Joany Marino

Elena Salogni

Adrian Richter

Carsten Oliver Schmidt

German Research Foundation (DFG SCHM 2744/3-1, SCHM 2744/9-1, SCHM 2744/3-4) 

National Research Data Infrastructure for Personal Health Data: (NFDI 13/1) 

European Union’s Horizon 2020 programme (euCanSHare, grant agreement No. 825903) 

int_part_vars_structure function

<dl><dt>study_data</dt>
<dd>study_data must have all relevant <code>PART_VARS</code> to avoid
false-positives on <code>PART_VARS</code> missing from
<code>study_data</code></dd>
<dt>meta_data</dt>
<dd>meta_data must be complete to avoid false positives on
non-existing <code>PART_VARS</code></dd>
<dt>label_col</dt>
<dd><a href="/link/character?package=dataquieR&version=2.1.0" data-mini-rdoc="dataquieR::character">character</a> mapping attribute <code>colnames(study_data)</code> vs.
<code>meta_data[label_col]</code></dd>
<dt>expected_observations</dt>
<dd>enum HIERARCHY | SEGMENT. How should
<code>PART_VARS</code> be handled:
- <code>SEGMENT</code>: if <code>PART_VAR</code> is 1, an
observation is expected
- <code>HIERARCHY</code>: the default, if the
<code>PART_VAR</code> is 1 for this variable and
also for all <code>PART_VARS</code> of <code>PART_VARS</code>
up in the hierarchy, an observation is
expected.</dd>
<dt>disclose_problem_paprt_var_data</dt>
<dd><a href="/link/logical?package=dataquieR&version=2.1.0" data-mini-rdoc="dataquieR::logical">logical</a> show the problematic data
(<code>PART_VAR</code> only)</dd></dl>

Arguments

Detect Expected Observations — int_part_vars_structure

<dl>

<dt>study_data</dt>
<dd>study_data must have all relevant <code>PART_VARS</code> to avoid
false-positives on <code>PART_VARS</code> missing from
<code>study_data</code></dd>


<dt>meta_data</dt>
<dd>meta_data must be complete to avoid false positives on
non-existing <code>PART_VARS</code></dd>


<dt>label_col</dt>
<dd><a href='https://rdrr.io/r/base/character.html'>character</a> mapping attribute <code>colnames(study_data)</code> vs.
<code>meta_data[label_col]</code></dd>


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


<dt>disclose_problem_paprt_var_data</dt>
<dd><a href='https://rdrr.io/r/base/logical.html'>logical</a> show the problematic data
(<code>PART_VAR</code> only)</dd>

</dl>

Detect Expected Observations

int_part_vars_structure: Detect Expected Observations

Description

Usage

Value

Arguments

Details