SDC-Report_v1

Input Data

The data set consists of 9948 observations

Information on selected important (key) variables

  • Categorical key variable(s): DISTRICT | URB_RUR | Crop_ID
  • Continuous key variable(s): not defined
  • Weight variable: HH_Final_weight
  • householdID: HOUSEHOLD_ID
  • strataVariable(s): not defined

Modifications

  • Modifications on categorical key variables: FALSE
  • Modifications on continuous key variables: NA
  • Modifications using PRAM: FALSE
  • Local suppressions: TRUE

Disclosure risk:

Frequency Analysis for Categorical Key Variables

Number of observations violating

  • 2-Anonymity: 0 (original dataset: 4)
  • 3-Anonymity: 0 (original dataset: 21)

Percentage of observations violating

  • 2-Anonymity: 0.000% (original dataset: 0.040%)
  • 3-Anonymity: 0.000% (original dataset: 0.211%)

Disclosure Risk for Categorical Variables

Expected Percentage of Reidentifications:

  • modified data: 0.011% (~ 1.119 observations)
  • original data: 0.014% (~ 1.387 observations)

10 combinations of categories with highest risks

DISTRICT URB_RUR Crop_ID risk fk Fk hier_risk
MOYAMBA Rural Cocoa 0.004 3 349.2412 0.0043899
MOYAMBA Urban Banana 0.004 5 328.9216 0.0037859
TONKOLILI Urban Krain Krain 0.004 3 404.5985 0.0047713
KAMBIA Urban Oil Palm 0.003 3 451.9014 0.0041251
FALABA Urban Oil Palm 0.003 3 470.8783 0.0033387
TONKOLILI Urban Sweet Peper 0.003 3 527.2700 0.0029280
TONKOLILI NA Coffee 0.003 3 547.1005 0.0043606
KAMBIA Urban Krain Krain 0.003 3 555.9193 0.0055060
FALABA Urban Millets 0.003 3 561.7391 0.0029426
PUJEHUN Urban Oil Palm 0.003 4 500.2000 0.0026585

Hierarchical risk

  • modified data: 4.161 (0.042%)
  • original data: 5.321 (0.053%)

Data Utility

Frequencies Categorical Key Variables:

Variable: DISTRICT

Categories Original data Modified data
KAILAHUN 1772 1772
KENEMA 1010 1009
KONO 1499 1498
BOMBALI 316 315
FALABA 372 371
KOINADUGU 132 132
TONKOLILI 1104 1104
KAMBIA 432 430
KARENE 288 287
PORTLOKO 675 674
BO 724 724
BONTHE 139 138
MOYAMBA 760 759
PUJEHUN 523 523
WESTERN RURAL 98 97
WESTERN URBAN 0 NA
NA 104 115

Variable: URB_RUR

Categories Original data Modified data
Rural 8238 8234
Urban 1378 1371
NA 332 343

Variable: Crop_ID

Categories Original data Modified data
Rice 3462 3462
Maize 604 604
Millets 74 74
Chilli Peper 200 200
Cucumber 180 180
Okra 163 163
Sweet Peper 110 110
Krain Krain 62 62
Potato leaves 87 87
Cocoa 975 975
Coffee 194 194
Kola 67 67
Banana 100 100
Groundnut 981 981
Soya Beans 74 74
Sesame(benie) 106 106
Oil Palm 743 743
Cassava 1114 1114
Yams 79 79
Broad beans 137 137
Other Cereal Crops 0 NA
Other Vegetable Crops 125 125
Other Fruits and Nuts Crops 136 136
Other Oil Seeds Crops 26 26
Other Tuber/Root Crops 87 87
Other Leguminous Crops 54 54
Other Industrial Crops 8 8

Local Suppressions

The table below shows for each categorical key variable the number (1st row) and the percentages (2nd row) of suppressed cells.

DISTRICT URB_RUR Crop_ID
Number of Suppression 11 11 0
Percentage 0.111 0.111 0.000

R-Code

Session-Info

About the R-Version

  • Version: R version 4.5.2 (2025-10-31 ucrt)
  • Platform: x86_64-w64-mingw32

Locales

LC_COLLATE=English_United States.utf8 | LC_CTYPE=English_United States.utf8 | LC_MONETARY=English_United States.utf8 | LC_NUMERIC=C | LC_TIME=English_United States.utf8

Attached base packages

stats | graphics | grDevices | utils | datasets | methods | base

Other attached packages

labelled (2.16.0) | questionr (0.8.1) | haven (2.5.5) | readxl (1.4.5) | tidyr (1.3.1) | dplyr (1.1.4) | agrisvyr (0.2.0) | sdcMicro (5.7.9)

Packages loaded via Namespace (but not attached)

tidyselect (1.2.1) | viridisLite (0.4.2) | farver (2.1.2) | R.utils (2.13.0) | S7 (0.2.1) | fastmap (1.2.0) | promises (1.5.0) | digest (0.6.38) | mime (0.13) | lifecycle (1.0.4) | cluster (2.1.8.1) | magrittr (2.0.4) | compiler (4.5.2) | rlang (1.1.6) | sass (0.4.10) | tools (4.5.2) | utf8 (1.2.6) | yaml (2.3.10) | data.table (1.17.8) | knitr (1.50) | askpass (1.2.1) | htmlwidgets (1.6.4) | plyr (1.8.9) | xml2 (1.4.1) | RColorBrewer (1.1-3) | miniUI (0.1.2) | withr (3.0.2) | purrr (1.2.0) | R.oo (1.27.1) | grid (4.5.2) | xtable (1.8-4) | data.tree (1.2.0) | ggplot2 (4.0.1) | scales (1.4.0) | MASS (7.3-65) | cli (3.6.5) | rmarkdown (2.30) | crayon (1.5.3) | generics (0.1.4) | otel (0.2.0) | rstudioapi (0.17.1) | robustbase (0.99-6) | tzdb (0.5.0) | cachem (1.1.0) | stringr (1.6.0) | rhandsontable (0.3.8) | cellranger (1.1.0) | vctrs (0.6.5) | jsonlite (2.0.0) | carData (3.0-5) | hms (1.1.4) | systemfonts (1.3.1) | jquerylib (0.1.4) | shinyBS (0.61.1) | glue (1.8.0) | DEoptimR (1.1-4) | DT (0.34.0) | stringi (1.8.7) | gtable (0.3.6) | later (1.4.4) | tibble (3.3.0) | pillar (1.11.1) | htmltools (0.5.8.1) | openssl (2.3.4) | R6 (2.6.1) | textshaping (1.0.4) | evaluate (1.0.5) | shiny (1.11.1) | kableExtra (1.4.0) | readr (2.1.6) | highr (0.11) | R.methodsS3 (1.8.2) | openxlsx (4.2.8.1) | renv (1.1.5) | httpuv (1.6.16) | bslib (0.9.0) | Rcpp (1.1.0) | zip (2.3.3) | svglite (2.2.2) | xfun (0.54) | fs (1.6.6) | forcats (1.0.1) | usethis (3.2.1) | getPass (0.2-4) | prettydoc (0.4.1) | pkgconfig (2.0.3)

Disclaimer

R-Package sdcMicro is developed and maintained by Statistics Austria (www.statistik.at).

Please use the issue-tracker on github to report any issues:


This report was generated on Fri, 10/04/2026 at 10:37:37.