Dear Statalisters,

I haven't done anova in Stata since the advent of great 'xt/mixed'. But for particular reason, I will have to now and it appears Stata's daunting anova' literature requires me to invest a good amount of time to understand defining error terms properly which I am lacking at the moment. Therefore looking for a quick advice. The study has each person (id) measured 4 times (visit), two treatment (trt) and a baseline variable (v1). when i run only with the treatmentXtime interaction the model runs fine:

Code:
anova y trt / id|trt visit visit#trt, repeated(visit)

           Number of obs =      1,155    R-squared     =  0.7359
                         Root MSE      =    4.54209    Adj R-squared =  0.6411

                  Source | Partial SS         df         MS        F    Prob>F
              -----------+----------------------------------------------------
                   Model |  48813.929        305   160.04567      7.76  0.0000
                         |
                     trt |   11.46467          1    11.46467      0.12  0.7340
                  id|trt |  29525.081        298   99.077452  
              -----------+----------------------------------------------------
                   visit |  18395.491          3   6131.8302    297.22  0.0000
               visit#trt |  40.231611          3   13.410537      0.65  0.5831
                         |
                Residual |   17515.35        849   20.630565  
              -----------+----------------------------------------------------
                   Total |  66329.279      1,154   57.477711
But whenever I add 'v1' in the model defining its error term within id it gives me error:

Code:
anova y trt / id|trt visit visit#trt v1 / id|trt, repeated(visit)
could not determine between-subject error term; use bse() option

Below the data example and any advice is appreciated. I guess I am not defining the error term properly:
Code:
* Example generated by -dataex-. To install: ssc install dataex

clear
input int id float(trt v1 visit y)
10001 0 0 0 17
10001 0 0 1  6
10001 0 0 2  7
10001 0 0 3  6
10006 0 0 0 22
10006 0 0 1 22
10006 0 0 2 20
10006 0 0 3 19
10009 0 0 0 16
10009 0 0 1 11
10009 0 0 2  6
10009 0 0 3  4
10011 0 0 0 15
10011 0 0 1  2
10011 0 0 2  1
10011 0 0 3  1
10012 0 1 0 16
10012 0 1 1 13
10012 0 1 2 12
10012 0 1 3  8
10013 0 0 0 21
10013 0 0 1 19
10013 0 0 2  .
10013 0 0 3  .
10015 0 0 0 18
10015 0 0 1 18
10015 0 0 2 17
10015 0 0 3 14
10016 0 0 0 14
10016 0 0 1 15
10016 0 0 2  5
10016 0 0 3  3
10019 0 1 0 15
10019 0 1 1  9
10019 0 1 2  2
10019 0 1 3  1
10040 0 1 0 25
10040 0 1 1 18
10040 0 1 2 22
10040 0 1 3  6
10042 0 0 0 11
10042 0 0 1 13
10042 0 0 2 16
10042 0 0 3  5
10071 0 0 0 20
10071 0 0 1  2
10071 0 0 2  3
10071 0 0 3 14
10080 0 1 0 24
10080 0 1 1  4
10080 0 1 2  3
10080 0 1 3 11
10089 0 0 0 10
10089 0 0 1  2
10089 0 0 2 15
10089 0 0 3 10
10091 0 0 0 18
10091 0 0 1  3
10091 0 0 2  2
10091 0 0 3  2
10095 0 0 0 21
10095 0 0 1 12
10095 0 0 2  8
10095 0 0 3 10
10108 0 1 0  9
10108 0 1 1  4
10108 0 1 2  7
10108 0 1 3  4
10112 0 1 0 11
10112 0 1 1  3
10112 0 1 2  7
10112 0 1 3 14
10125 0 0 0 18
10125 0 0 1  6
10125 0 0 2  3
10125 0 0 3  9
10126 0 0 0 24
10126 0 0 1 18
10126 0 0 2 19
10126 0 0 3  .
10127 0 0 0 11
10127 0 0 1 12
10127 0 0 2 11
10127 0 0 3 13
10129 0 1 0 26
10129 0 1 1 14
10129 0 1 2  7
10129 0 1 3 12
10138 0 0 0 20
10138 0 0 1 21
10138 0 0 2 18
10138 0 0 3 20
10145 0 1 0 19
10145 0 1 1  7
10145 0 1 2  7
10145 0 1 3  3
10151 0 1 0 17
10151 0 1 1  5
10151 0 1 2  7
10151 0 1 3  .
end