syn.satcat: Synthesis from a saturated model based on all combinations of...

In synthpop: Generating Synthetic Versions of Sensitive Microdata for Statistical Disclosure Control

Synthesis from a saturated model based on all combinations of the predictor variables.

Description

Synthesises one variable (y) from all possible combinations of its precitors (x). A bootstrap sample is created from the original values of y within each unique combinations of of xp (the syntheisied values of the grouping variable).

Usage

syn.satcat(y, x, xp, proper = FALSE, ...)

Arguments

y	an original data vector of length n for the satcat variable.
x	a matrix (n x p) with the original predictor variables for y.
xp	a matrix (k x p) with synthetic values of x.
proper	if proper = TRUE x and y are replaced with a bootstrap sample before synthesis, thus effectively sampling from the posterior distribution of the model, given the data.
...	additional parameters.

Details

It is intended that the variables in x are categorical (factor) variables. If y is also a categorical variable syn.satcat will give the same results as fitting a saturated polychotomous regression model but will usually be much faster. syn.satcat will fail with an error message if previous syntheses have generated a combination of variables in xp that was not present in x. Use of the syn.catall method for grouped variables can overcome this.

Value

A list with two components:

res	a data frame of dimension k x p containing the synthesised data.
fit	the cross-tabulation of the original predictor variables.

Examples

ods <- SD2011[, c("region", "sex", "agegr", "placesize")]

s1 <- syn(ods, method = c("sample", "cart", "satcat", "cart"))

## Not run: 
### mostly fails because too many small categories
s2 <- syn(ods, method = c("sample", "cart", "cart", "satcat"))
## End(Not run)

synthpop documentation built on Aug. 31, 2022, 5:06 p.m.