Given the dismal history of anonymization, a paper on arvix is roughly up there with a blogger saying 'I've proven p!=np'...
> It's guaranteed not to screw up your observations because, by definition, if something is statistically significant it has to show up often enough that it CANT be used to single out a source.
What's 'statistically significant' here? The usual p<0.05 convention? You realize that there can be multiple measurements or pieces of data all of which individually have p>0.05 but together have p<<0.05... Information leakage should be measured in bits, not p-values.
(This kind of aggregation is one of the benefits of approaches like meta-analysis.)
Comments
Given the dismal history of anonymization, a paper on arvix is roughly up there with a blogger saying 'I've proven p!=np'...
> It's guaranteed not to screw up your observations because, by definition, if something is statistically significant it has to show up often enough that it CANT be used to single out a source.
What's 'statistically significant' here? The usual p<0.05 convention? You realize that there can be multiple measurements or pieces of data all of which individually have p>0.05 but together have p<<0.05... Information leakage should be measured in bits, not p-values.
(This kind of aggregation is one of the benefits of approaches like meta-analysis.)