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st: Adjust produced blank table after performing repeated measures ANOVA


From   Janine Jones <janine.jones@adelaide.edu.au>
To   statalist@hsphsun2.harvard.edu
Subject   st: Adjust produced blank table after performing repeated measures ANOVA
Date   Tue, 20 Sep 2005 15:07:52 +0930

I have a performed a repeated measures ANOVA. My problem is that if I
want to get the adjusted means for the three-way interaction (it isn't
significant in this example but assume it was) diab*currshoulder*time
using the function adjust it produces a blank table as shown below.
However I understand it has something to do with my between-subjects
error term labelled uid. How can I get my 3 way interaction means at the
average age but also at the 'average' uid/subject(centering the uid
effect at zero)?

I have attached the example dataset.

Thanks,
Janine.



. anova spadi age diab currshoulder diab*currshoulder /
uid|diab*currshoulder time diab*time currshoulder*ti
> me diab*currshoulder*time, continuous(age) repeated(time) sequential

                           Number of obs =     558     R-squared     = 
0.8701
                           Root MSE      = 11.2057     Adj R-squared = 
0.7620

                  Source |    Seq. SS     df       MS           F    
Prob > F
  
----------------------+----------------------------------------------------
                   Model |  255678.229   253  1010.58589       8.05    
0.0000
                         |
                     age |  4830.84766     1  4830.84766       7.25    
0.0076
                    diab |  8418.50341     1  8418.50341      12.63    
0.0005
             currshoul~r |  75854.8577     1  75854.8577     113.83    
0.0000
        diab*currshoul~r |  1118.32523     1  1118.32523       1.68    
0.1964
    uid|diab*currshoul~r |   160593.71   241  666.363943   
  
----------------------+----------------------------------------------------
                    time |  3988.74315     2  1994.37158      15.88    
0.0000
               diab*time |  402.488385     2  201.244192       1.60    
0.2031
        currshoul~r*time |  295.765196     2  147.882598       1.18    
0.3094
   diab*currshoul~r*time |  174.987866     2   87.493933       0.70    
0.4990
                         |
                Residual |  38172.7318   304  125.568197   
  
----------------------+----------------------------------------------------
                   Total |  293850.961   557  527.560073   


Between-subjects error term:  uid|diab*currshoul~r
                     Levels:  246       (241 df)
     Lowest b.s.e. variable:  uid
     Covariance pooled over:  diab*currshoul~r  (for repeated variable)

Repeated variable: time
                                          Huynh-Feldt epsilon        = 
0.9959
                                          Greenhouse-Geisser epsilon = 
0.9719
                                          Box's conservative epsilon = 
0.5000

                                            ------------ Prob > F
------------
                  Source |     df      F    Regular    H-F      G-G     
Box
  
----------------------+----------------------------------------------------
                    time |      2    15.88   0.0000   0.0000   0.0000  
0.0001
               diab*time |      2     1.60   0.2031   0.2032   0.2038  
0.2075
        currshoul~r*time |      2     1.18   0.3094   0.3093   0.3085  
0.2795
   diab*currshoul~r*time |      2     0.70   0.4990   0.4984   0.4951  
0.4052
                Residual |    304
  
----------------------+----------------------------------------------------

. adjust age, by(diab currshoulder time)

------------------------------------------------------------------------------------------------------------
     Dependent variable: spadi     Command: anova
    Variable left as is: uid
  Covariate set to mean: age = 59.180023
------------------------------------------------------------------------------------------------------------

--------------------------------------------------
          |         time! and currshoulder        
          | ---- 0 ---    ---- 6 ---    --- 12 ---
     diab |    0     1       0     1       0     1
----------+---------------------------------------
        0 |                                       
        1 |                                       
--------------------------------------------------
     Key:  Linear Prediction

.

Attachment: example.dta
Description: application/unknown-content-type-stata9data




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