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Running /home/krg/bin/profile.do ...
Compile number 170082

. do sl2.do 

. /* NIST/ITL StRD
> 
> ANOVA
> 
> Difficulty=Lower  n_i=201  k=9  Generated
> 
> Dataset Name:   Simon-Lesage2   (Simon-Lesage2.dat)
> 
> 
> File Format:    ASCII
>                 Certified Values   (lines 41 to 47)
>                 Data               (lines 61 to 1869)
> 
> 
> Procedure:      Analysis of Variance
> 
> 
> Reference:      Simon, Stephen D. and Lesage, James P. (1989).
>                 "Assessing the Accuracy of ANOVA Calculations in
>                 Statistical Software".
>                 Computational Statistics & Data Analysis, 8, pp. 325-332.
> 
> 
> Data:           1 Factor
>                 9 Treatments
>                 201 Replicates/Cell
>                 1809 Observations
>                 1 Constant Leading Digit
>                 Lower Level of Difficulty
>                 Generated Data
> 
> 
> Model:          10 Parameters (mu,tau_1, ... , tau_9)
>                 y_{ij} = mu + tau_i + epsilon_{ij}
> 
> 
> Certified Values:
> 
> Source of                  Sums of               Mean
> Variation          df      Squares              Squares             F Statist
> ic
> 
> Between Treatment    8 1.60800000000000E+01 2.01000000000000E+00
> 2.01000000000000E+02
> Within Treatment  1800 1.80000000000000E+01 1.00000000000000E-02
> 
>                   Certified R-Squared 4.71830985915493E-01
> 
>                   Certified Residual
>                   Standard Deviation  1.00000000000000E-01
> */
. 
. clear

. 
. scalar N         = 1809

. scalar df_r      = 1800

. scalar df_m      = 8

. 
. scalar mss       = 16.08

. scalar F         = 201

. scalar rss       = 18

. scalar r2        = 4.71830985915493E-01

. scalar rmse      = 0.1

. 
. qui input byte treat double resp

. 
. anova resp treat

                         Number of obs =      1,809    R-squared     =  0.4718
                         Root MSE      =         .1    Adj R-squared =  0.4695

                  Source | Partial SS         df         MS        F    Prob>F
              -----------+----------------------------------------------------
                   Model |      16.08          8        2.01    201.00  0.0000
                         |
                   treat |      16.08          8        2.01    201.00  0.0000
                         |
                Residual |         18      1,800         .01  
              -----------+----------------------------------------------------
                   Total |      34.08      1,808   .01884956  

. 
. assert N    == e(N)

. assert df_r == e(df_r)

. assert df_m == e(df_m)

. 
. lrecomp e(F) F e(rmse) rmse e(r2) r2 e(mss) mss e(rss) rss

e(F)                13.6
e(rmse)             15.6
e(r2)               13.9
e(mss)              13.6
e(rss)              15.2

. 
end of do-file