Function Use Statistics

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Some versions of PLS_Toolbox and Solo allow you to contribute anonymous "Feature Use" information to the Eigenvector Research development team. This information is ONLY used to help us better understand which features are most used and, therefore, where our development effort is best spent in improving our tools.

Opt-In

This feature is completely "opt-in" meaning that it will NOT collect or send any information unless you explicitly tell it that you want to participate. Once you've been asked once, it will not ask you again (unless you clear all program settings, for example, if you uninstall and re-install from scratch.) Under no circumstances will it ever send use information unless you have explicitly told it you want to do so.

This feature has no impact on performance of the software. If it cannot file a report, it will simply discard the information.

It can be disabled (and re-enabled) through the Help menu in the Workspace Browser or the Analysis window.

What Information Is Not Collected?

The information collected by this feature includes absolutely NO information about: your data, you, your computer, your company/affiliated organization, your location, your IP address, your Eigenvector Research account or license number, nor any other personally-identifiable information.

What Information Is Collected?

The report includes the number of times you made use of particular features in the software and combines this count with the product name (e.g. "PLS_Toolbox", "Solo", "Solo+MIA"), version number, and whether the given product is running with an expiring "Demo" license code. This information is periodically sent to Eigenvector Research (e.g. every 30 minutes) along with a random code allowing the system to combine the reports.

Example Report

Below is an example of a report collected by one of the Eigenvector Research staff during a short period of time:

      cumulative: 152
     peakfindgui: 12
 plotgui_toolbar: 11
      drop_parse: 2
      figbrowser: 13
       evrimodel: 2
         explode: 22
        analysis: 30
      pca_guifcn: 4
            auto: 1
         normset: 1
  wlsbaselineset: 3
     wlsbaseline: 1
        baseline: 1
    poissonscale: 1
          flucut: 1
         emscorr: 1
         mdcheck: 8
             pca: 6
      evriscript: 1
       pcaengine: 3
   residuallimit: 2
      choosecomp: 2
      modelcache: 3
      plotscores: 2
  plotscores_pca: 2
knnscoredistance: 2
    inheritimage: 1
           mplot: 2
         plotgui: 2
         evritip: 3
    classmarkers: 1
       plotloads: 2
           scale: 2