When you install a managed package with a post-install script, Salesforce creates a special ghost user under which all of the post install activities occur. I think this is undocumented. Here are some details.

This can be great from an audit point of view (you can see which package has 'touched' all the data). But can problematic in several examples:


Certain objects are inaccessible by SOQL (I've found CronTrigger and ApexClass so far)
Scheduled Jobs (and any code they call) will forever run under the post-install context,
Batch Jobs execute as the post-install user and suffer the same issues above,


I've tried querying the user by id in SOQL to no avail, and the debug log monitor don't record anything.

How crippled is this special ghost user? Does he have a documented profile?

Edit: I've emailed myself some post install context UserInfo return values. Interesting ones in bold:


UserType: LicenseManager (Aha! Who knows what privileges he has!?)
ProfileId: 00eF0000000XXXXAAA (viewing URL gives Insufficient Privileges!)
UserName: 033g0000000XXXXAAA@00df0000000XXXXAAA (package-id@org-id)
UserId: 005F0000003XXXXAAA (viewing URL gives Insufficient Privileges!)
Email: noreply@salesforce.com
DefaultCurrency: USD
FirstName: null
Language: en_US
LastName: [managed package name]
Locale: en_US
Name: [managed package name]
OrganizationId: [installing org id]
OrganizationName: [installing company name]
SessionId: null
TimeZone: America/Los_Angeles
UiTheme: Theme3
UiThemeDisplayed: Theme3
UserRoleId: null



Question: How to describe the differences in skewed data with same median but statistically different distribution?
Answer: The same question has been discussed on the Google-group Medstats. 

It was suggested that the arithmetic mean should be used as this is a more useful measure for planners. A difference in LOS of 0.3 days can be important for planning of health services and cost. Geometric and harmonic mean were dismissed as not correct to use in this situation. 

Different approaches was proposed for modelling using quantile or Cox-regression. 

I proposed poisson regression but ended up with negative binomial regression as the data showed evidence of overdispersion. This allowed me to compare the unadjusted difference of 0.3 days with difference after adjusting for age, sex, perforated appendicitis and period, which came down to a difference of only 0.05 days between the two surgical methods. This is important findings (although negative) as it goes against the common thinking about the advantages of laparoscopic appendectomy