util_eval_rule

also allows to use <code>VAR_NAMES</code> in the rules,
if other labels have been selected

internal

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) 

util_eval_rule function

<dl><dt>rule</dt>
<dd>the redcap rule (parsed, already)</dd>
<dt>ds1</dt>
<dd>the study data as prepared by <code>prep_prepare_dataframes</code></dd>
<dt>meta_data</dt>
<dd>the metadata</dd>
<dt>use_value_labels</dt>
<dd>map columns with <code>VALUE_LABELS</code> as factor variables</dd>
<dt>replace_missing_by</dt>
<dd>enum LABEL | INTERPRET | NA . Missing codes should
be replaced by the missing labels, the
<code>AAPOR</code> codes from the missing table or
by <code>NA</code>. Can also be an empty string to keep
the codes.</dd>
<dt>replace_limits</dt>
<dd><a href="/link/logical?package=dataquieR&version=2.1.0" data-mini-rdoc="dataquieR::logical">logical</a> replace hard limit violations by <code>NA</code></dd></dl>

Arguments

Evaluate a parsed redcap rule for given study data — util_eval_rule

<dl>

<dt>rule</dt>
<dd>the redcap rule (parsed, already)</dd>


<dt>ds1</dt>
<dd>the study data as prepared by <code>prep_prepare_dataframes</code></dd>


<dt>meta_data</dt>
<dd>the metadata</dd>


<dt>use_value_labels</dt>
<dd>map columns with <code>VALUE_LABELS</code> as factor variables</dd>


<dt>replace_missing_by</dt>
<dd>enum LABEL | INTERPRET | NA . Missing codes should
be replaced by the missing labels, the
<code>AAPOR</code> codes from the missing table or
by <code>NA</code>. Can also be an empty string to keep
the codes.</dd>


<dt>replace_limits</dt>
<dd><a href='https://rdrr.io/r/base/logical.html'>logical</a> replace hard limit violations by <code>NA</code></dd>

</dl>

Evaluate a parsed redcap rule for given study data

util_eval_rule: Evaluate a parsed redcap rule for given study data

Description

Usage

Value

Arguments

See Also