st: -adjust- command with pr after logistic not giving correct output?

[Kaleb Michaud <kaleb@arthritis-research.org>]

There appears to be a problem with either my interpretation of what output 
the -adjust- command should give or in the actual program itself.  It only 
shows itself when using the pr (probability) option after a logistic 
command (used in this example).

Below I've used a sample Stata data set (census), created a binary variable 
(longer) and then did a logistic using a single dependent variable 
(medage).  I then use -predict- with the pr option to create the p1 
variable.  Using -adjust- without setting any values and using the pr 
option, I generate the a1 variable and the output from -adjust- is by a 
small categorical variable (region).  Lastly, I display the average values 
of p1 and a1 by region (using -tabstat-) and they are exactly the same, but 
they differ from the output from -adjust-.

Though the numbers seem similar, I am getting much larger and important 
differences (~0.005) with my dataset of >10K observations.  Also, doing 
these examples with the xb option gives output that are exactly the same - 
the problem seems limited to the pr option.

I look forward to any advice you can give.
Sincerely,
Kaleb Michaud
Arthritis Research Center


. use census
(1980 Census data by state)

. gen longer = length(state)

. recode longer min/8=0 9/max=1
(50 changes made)

. logistic longer medage

Logit estimates                                   Number of obs   =         50
                                                  LR chi2(1)      =       0.58
                                                  Prob > chi2     =     0.4481
Log likelihood = -32.915529                       Pseudo R2       =     0.0087

------------------------------------------------------------------------------
      longer | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      medage |   1.143314   .2048402     0.75   0.455     .8047506    1.624314
------------------------------------------------------------------------------

. predict p1 if e(sample), pr

. adjust, by(region) pr gen(a1)

------------------------------------------------------------------------------
     Dependent variable: longer     Command: logistic
       Created variable: a1
    Variable left as is: medage
------------------------------------------------------------------------------

----------------------
Census    |
region    |         pr
----------+-----------
       NE |    .433217
  N Cntrl |     .37812
    South |    .381077
     West |    .339917
----------------------
     Key:  pr  =  Probability

. tabstat p1 a1 medage, by(region)

Summary statistics: mean
  by categories of: region (Census region)

 region |        p1        a1    medage
--------+------------------------------
     NE |  .4335186  .4335186  31.23333
N Cntrl |  .3783487  .3783487    29.525
  South |  .3821012  .3821012  29.61875
   West |  .3418868  .3418868  28.28462
--------+------------------------------
  Total |       .38       .38     29.54
---------------------------------------


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