ck_dat_hc92

820000 obervations in 5 Variables without sampling weights.

datasets

Data from statistical agencies and other institutions often
need to be protected before they can be published. This package
can be used to perturb statistical tables in a consistent way. The
main idea is to add - at the micro data level - a record key for each
unit. Based on these keys, for any cell in a statistical table a
cell key is computed as a function on the record keys contributing to
a specific cell. Values that are added to the cell in order to perturb
it are derived from a lookup-table that maps values of cell keys to
specific perturbation values. The theoretical basis for the methods
implemented can be found in Thompson, Broadfoot and Elazar
(2013) <https://unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2013/Topic_1_ABS.pdf>
which was extended and enhanced by Giessing and Tent
(2019) <https://unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2019/mtg1/SDC2019_S2_Germany_Giessing_Tent_AD.pdf>.

Bernhard Meindl

cellKey

Consistent Perturbation of Statistical Frequency- And Magnitude
Tables

ck_dat_hc92 function

ck_dat_hc92: a data frame with 820000 observations on the following 6 variables.<ul>
<li><code>id</code>: a numeric identifier</li>
<li><code>geo_m</code>: a character vector defining regions</li>
<li><code>sex a</code>: character vector defining gender</li>
<li><code>age_m</code>: a character vector containing age groups</li>
<li><code>yae_h</code>: a character vector</li>
<li><code>rkey</code>: a numeric vector holding record keys</li>
</ul>

ck_dat_hc92: A real-world data set on persons

Description

Arguments

Format

References

Examples