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First of all thanks a lot for your amazing and extensive package. I was wondering whether there is already a way to allow for variable group size when doing microaggregation? If not - are you planning on implementing it?
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Thank you, this is an interesting comment and suggestion. However, may I ask what is the rationale behind such an approach? Typically we have a disclosure scenario and depending on that we set a fixed value for the group size, i.e. a fixed group size is motivated from a "k-anonymity" view. Are there matching scenarios where different group sizes are essential? I wonder if you may argue with outliers and homogeneity of groups? If I would see a need from an application/case then we surely want to implement it, otherwise, we would stay with the fixed group size only.
Thank you very much for your quick response. Of course! My rationale is that in the company I am working for (a large state-owned enterprise) the data protection rules define a minimum group size rather than a fixed size. In my humble experience and my application, I do not see a reason why to use a fixed size (except for computational reasons) and it seems to me in a way arbitrary. I might end up assigning an observation to a group simply because the most similar group already reached its fixed size. Is this comprehensible?
First of all thanks a lot for your amazing and extensive package. I was wondering whether there is already a way to allow for variable group size when doing microaggregation? If not - are you planning on implementing it?
The text was updated successfully, but these errors were encountered: