SDC-Report_v1

Input Data

The data set consists of 56029 observations

Information on selected important (key) variables

  • Categorical key variable(s): DISTRICT | URB_RUR | S7A_PID
  • Continuous key variable(s): Total_qty_collected | Total_qty_used | Total_qty_sold
  • Weight variable: HH_Final_weight
  • householdID: HOUSEHOLD_ID
  • strataVariable(s): not defined

Modifications

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

Disclosure risk:

Frequency Analysis for Categorical Key Variables

Number of observations violating

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

Percentage of observations violating

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

Disclosure Risk for Categorical Variables

Expected Percentage of Reidentifications:

  • modified data: 0.003% (~ 1.557 observations)
  • original data: 0.003% (~ 1.557 observations)

10 combinations of categories with highest risks

DISTRICT URB_RUR S7A_PID risk fk Fk hier_risk
MOYAMBA Urban 1 0.001 10 1941.628 0.0108109
MOYAMBA Urban 2 0.001 10 1941.628 0.0108109
MOYAMBA Urban 3 0.001 10 1941.628 0.0108109
MOYAMBA Urban 4 0.001 10 1941.628 0.0108109
MOYAMBA Urban 5 0.001 10 1941.628 0.0108109
MOYAMBA Urban 6 0.001 10 1941.628 0.0108109
MOYAMBA Urban 7 0.001 10 1941.628 0.0108109
MOYAMBA Urban 8 0.001 10 1941.628 0.0108109
MOYAMBA Urban 9 0.001 10 1941.628 0.0108109
MOYAMBA Urban 10 0.001 10 1941.628 0.0108109

Disclosure Risk Continuous Scaled Variables

The (distance-based) disclosure risk for continous key variables is between 0.000% and 99.416% in the modified data.

In the original data, the risk is assumed to be approximately 100.000%.

Hierarchical risk

  • modified data: 29.560 (0.053%)
  • original data: 29.560 (0.053%)

Data Utility

Frequencies Categorical Key Variables:

Variable: DISTRICT

Categories Original data Modified data
KAILAHUN 10146 10146
KENEMA 7296 7296
KONO 7638 7638
BOMBALI 1670 1670
FALABA 2717 2717
KOINADUGU 1425 1425
TONKOLILI 3895 3895
KAMBIA 3249 3249
KARENE 1653 1653
PORTLOKO 3914 3914
BO 4731 4731
BONTHE 1178 1178
MOYAMBA 2717 2717
PUJEHUN 3306 3306
WESTERN RURAL 133 133
WESTERN URBAN 0 NA
NA 361 361

Variable: URB_RUR

Categories Original data Modified data
Rural 47403 47403
Urban 7676 7676
NA 950 950

Variable: S7A_PID

Categories Original data Modified data
1 2949 2949
10 2949 2949
11 2949 2949
12 2949 2949
13 2949 2949
14 2949 2949
15 2949 2949
16 2949 2949
17 2949 2949
18 2948 2948
19 2948 2948
2 2949 2949
3 2949 2949
4 2949 2949
5 2949 2949
6 2949 2949
7 2949 2949
8 2949 2949
9 2949 2949

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 S7A_PID
Number of Suppression 0 0 0
Percentage 0.000 0.000 0.000

Data Utility of Continuous Scaled Key Variables

Univariate summary of variable Total_qty_collected

Original Modified Difference
Min. 3.000 3.0 0.000
1st Qu. 202.240 202.2 0.040
Median 632.000 632.0 0.000
Mean 7400.566 3057.1 4343.466
3rd Qu. 3148.800 3148.8 0.000
Max. 1093950.000 18445.0 1075505.000

Univariate summary of variable Total_qty_used

Original Modified Difference
Min. 0.00 0.0 0.0000
1st Qu. 37.92 37.9 0.0200
Median 126.40 126.4 0.0000
Mean 1350.06 961.0 389.0603
3rd Qu. 613.80 613.8 0.0000
Max. 121550.00 12240.0 109310.0000

Univariate summary of variable Total_qty_sold

Original Modified Difference
Min. 2.000 2.0 0.000
1st Qu. 136.000 136.0 0.000
Median 422.840 422.8 0.040
Mean 6045.746 2282.9 3762.846
3rd Qu. 2209.680 2209.7 -0.020
Max. 1069640.000 14382.0 1055258.000

Information Loss Criteria

  • Criteria IL1: 21743.789%
  • Difference of Eigenvalues in modified data: -29.701% (0.00% in original data)

Boxplot of Differences

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 Wed, 08/04/2026 at 23:34:05.