acc_end_digits

This implementation contrasts the empirical distribution of a measurement
variables against assumed distributions. The approach is adapted from the
idea of rootograms (Tukey (1977)) which is also applicable for count data
(Kleiber and Zeileis (2016)).
Indicator

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) 

acc_end_digits function

<dl><dt>resp_vars</dt>
<dd>variable the names of the measurement variables,
mandatory</dd>
<dt>study_data</dt>
<dd><a href="/link/data.frame?package=dataquieR&version=2.1.0" data-mini-rdoc="dataquieR::data.frame">data.frame</a> the data frame that contains the measurements</dd>
<dt>meta_data</dt>
<dd><a href="/link/data.frame?package=dataquieR&version=2.1.0" data-mini-rdoc="dataquieR::data.frame">data.frame</a> the data frame that contains metadata
attributes of study data</dd>
<dt>label_col</dt>
<dd>variable attribute the name of the column in the metadata
with labels of variables</dd></dl>

Arguments

<ul>
<li>This implementation is restricted to data of type float or integer.</li>
<li>Missing codes are removed from resp_vars (if defined in the metadata)</li>
<li>The user must specify the column of the metadata containing probability
distribution (currently only: normal, uniform, gamma)</li>
<li>Parameters of each distribution can be estimated from the data or are
specified by the user</li>
<li>A histogram-like plot contrasts the empirical vs. the technical
distribution</li>
</ul>

ALGORITHM OF THIS IMPLEMENTATION:

Extension of acc_shape_or_scale to examine uniform distributions of
end digits — acc_end_digits

<dl>

<dt>resp_vars</dt>
<dd>variable the names of the measurement variables,
mandatory</dd>


<dt>study_data</dt>
<dd><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> the data frame that contains the measurements</dd>


<dt>meta_data</dt>
<dd><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> the data frame that contains metadata
attributes of study data</dd>


<dt>label_col</dt>
<dd>variable attribute the name of the column in the metadata
with labels of variables</dd>

</dl>

acc_end_digits: Extension of acc_shape_or_scale to examine uniform distributions of end digits

Description

Usage

Value

Arguments

ALGORITHM OF THIS IMPLEMENTATION:

See Also