synthpop: Generating Synthetic Versions of Sensitive Microdata for Statistical Disclosure Control
A tool for producing synthetic versions of microdata containing confidential information so that they are safe to be released to users for exploratory analysis. The key objective of generating synthetic data is to replace sensitive original values with synthetic ones causing minimal distortion of the statistical information contained in the data set. Variables, which can be categorical or continuous, are synthesised one-by-one using sequential modelling. Replacements are generated by drawing from conditional distributions fitted to the original data using parametric or classification and regression trees models. Data are synthesised via the function syn() which can be largely automated, if default settings are used, or with methods defined by the user. Optional parameters can be used to influence the disclosure risk and the analytical quality of the synthesised data.
- Beata Nowok, Gillian M Raab, Joshua Snoke and Chris Dibben
- Date of publication
- 2016-03-15 15:10:21
- Beata Nowok <email@example.com>
- GPL-2 | GPL-3
- Comparison of synthesised and observed data
- Compare model estimates based on synthesised and observed...
- Compare univariate distributions of synthesised and observed...
- Fitting (generalized) linear models to synthetic data
- Importing original data sets form external files
- Replications in synthetic data
- Social Diagnosis 2011 - Objective and Subjective Quality of...
- Tools for statistical disclosure control (sdc)
- Inference from synthetic data
- Synthetic data object summaries
- Generating synthetic data sets
- Synthesis with bagging
- Synthesis with classification and regression trees (CART)
- Synthesis by linear regression after transformation of a...
- Synthesis by logistic regression
- Synthesis by linear regression
- Synthesis by normal linear regression preserving the marginal...
- Passive synthesis
- Synthesis by predictive mean matching
- Synthesis by ordered polytomous regression
- Synthesis by unordered polytomous regression
- Synthesis with random forest
- Synthesis by simple random sampling
- Synthesis of survival time by classification and regression...
- Generating synthetic versions of sensitive microdata for...
- Distributional comparison of synthesised and observed data
- Exporting synthetic data sets to external files
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