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vazul is an R package for analyis blinding in research contexts. It offers two main approaches to anonymize data while preserving analytical validity: masking (replacing values with anonymous labels) and scrambling (randomizing the order of existing values).
Masking replaces original values with anonymous labels, completely hiding the original information:
treatment <- c("control", "treatment", "control")
mask_labels(treatment)
#> "masked_group_01" "masked_group_02" "masked_group_01"Scrambling preserves all original values but randomizes their order:
scramble_values(treatment)
#> "treatment" "control" "control" # Same values, different orderYou can install the released version of vazul from CRAN with:
install.packages("vazul")Or the development version from GitHub with:
remotes::install_github("nthun/vazul")Replace categorical values with anonymous labels to completely hide original information.
mask_labels() -
Mask vector valueslibrary(vazul)
# Basic masking
treatment <- c("control", "treatment", "control", "treatment")
set.seed(123)
mask_labels(treatment)
#> "masked_group_01" "masked_group_02" "masked_group_01" "masked_group_02"
# Custom prefix
mask_labels(treatment, prefix = "group_")
#> "group_01" "group_02" "group_01" "group_02"mask_variables()
- Mask data frame columnsdf <- data.frame(
condition = c("A", "B", "A", "B"),
treatment = c("ctrl", "test", "ctrl", "test"),
score = c(85, 92, 78, 88)
)
# Mask multiple columns
mask_variables(df, c("condition", "treatment"))
# Use tidyselect helpers
mask_variables(df, where(is.character))The .across_variables parameter allows for consistent
masking across multiple columns (e.g., longitudinal data in wide
format).
df <- data.frame(
wave_1 = c("A", "B", "A"),
wave_2 = c("B", "A", "B"),
score = c(10, 20, 30)
)
# Mask across variables consistently
mask_variables(df, starts_with("wave_"), .across_variables = TRUE)Randomize the order of values while preserving the original data content.
scramble_values()
- Scramble vector order# Numeric data
set.seed(123)
scramble_values(1:5)
#> [1] 3 2 5 4 1
# Categorical data
scramble_values(c("A", "B", "C", "A", "B"))
#> [1] "B" "A" "C" "B" "A"scramble_variables()
- Scramble data frame columnsdf <- data.frame(x = 1:6, group = rep(c("A", "B"), each = 3))
# Scramble across entire column
scramble_variables(df, "x")
# Scramble within groups
scramble_variables(df, "x", .groups = "group")
# Using dplyr grouping
library(dplyr)
df |> group_by(group) |> scramble_variables("x").byrow = TRUE to shuffle values within each
row across the selected columns.df_items <- data.frame(
item1 = c(1, 4, 7),
item2 = c(2, 5, 8),
item3 = c(3, 6, 9)
)
# Shuffles values horizontally within each row
scramble_variables(df_items, item1:item3, .byrow = TRUE)Many Analysts Religion Project data: 10,535 participants across 24 countries studying religiosity and well-being.
Experimental study data: 112 participants examining risk-taking behavior under different wealth conditions.
Vazul was a Hungarian prince in the 11. century. He was blinded by the king to become unfit for the throne. More info: https://en.wikipedia.org/wiki/Vazul
?mask_labels,
?scramble_values, etc.Nagy, T., Kovács, M., & Sarafoglou, A. (2026). vazul: An R package for analysis blinding. Zenodo. https://doi.org/10.5281/zenodo.18269711
MIT License - see LICENSE file for details.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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