deidentify_data

Deidentify a dataset
Two operations are performed on the dataset:<ol>
<li>All ID numbers are randomized from the range 1 to n</li>
<li>All columns containing dates will have the year changed</li>
</ol>The year change is done by letting the earliest year in the dataset
be used as a reference and by maintaining leap years. The reference year
will either be 1901, 1902, 1903 or 1904 depending on its distance to the closest
preceeding leap year.

Interface to the 'Pharmpy' 'pharmacometrics' library. The 'Reticulate' package is used to interface Python from R.

Rikard Nordgren

pharmr

Interface to the 'Pharmpy' 'Pharmacometrics' Library

Stella Belin

Mats O. Karlsson

Andrew C. Hooker

Xiaomei Chen

Sebastian Ueckert

Simon Buatois

João A. Abrantes

Emilie Schindler

F. Hoffmann-La Roche Ltd. 

Bayer AG 

deidentify_data function

<dl><dt>df</dt>
<dd>(data.frame) A dataset</dd>
<dt>id_column</dt>
<dd>(str) Name of the id column</dd>
<dt>date_columns</dt>
<dd>(array(str) (optional)) Names of all date columns</dd></dl>

Arguments

Deidentify a dataset
Two operations are performed on the dataset:<ol>
<li>All ID numbers are randomized from the range 1 to n</li>
<li>All columns containing dates will have the year changed</li>
</ol>

The year change is done by letting the earliest year in the dataset
be used as a reference and by maintaining leap years. The reference year
will either be 1901, 1902, 1903 or 1904 depending on its distance to the closest
preceeding leap year.

deidentify_data — deidentify_data

<dl>

<dt>df</dt>
<dd>(data.frame) A dataset</dd>


<dt>id_column</dt>
<dd>(str) Name of the id column</dd>


<dt>date_columns</dt>
<dd>(array(str) (optional)) Names of all date columns</dd>

</dl>

deidentify_data: deidentify_data

Description

Usage

Value

Arguments