___  ____  ____  ____  ____ tm
 /__    /   ____/   /   ____/
___/   /   /___/   /   /___/    9.0   Copyright 1984-2005
  Statistics/Data Analysis            StataCorp
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                                      College Station, Texas 77845 USA
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3-user Stata for Linux64 (network) perpetual license:
       Serial number:  999
         Licensed to:  Brian P. Poi, Ph.D.
                       StataCorp LP

Notes:
      1.  (-m# option or -set memory-) 1.00 MB allocated to data
      2.  Command line editing disabled
      3.  Stata running in batch mode


running /home/bpp/bin/profile.do ...

. do sl1.do 

. /* NIST StRD benchmark from http://www.nist.gov/itl/div898/strd/
> 
> ANOVA
> 
> Difficulty=Lower  n_i=21  k=9  Generated
> 
> Dataset Name:   Simon-Lesage1   (Simon-Lesage1.dat)
> 
> 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
>                 21 Replicates/Cell
>                 189 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 Statisti
> c
> 
> Between Treatment   8 1.68000000000000E+00 2.10000000000000E-01 2.1000000000E
> +01
> Within Treatment  180 1.80000000000000E+00 1.00000000000000E-02
> 
>                   Certified R-Squared 4.82758620689655E-01
> 
>                   Certified Residual
>                   Standard Deviation  1.00000000000000E-01
> */
. 
. clear

. 
. scalar N         = 189

. scalar df_r      = 180

. scalar df_m      = 8

. 
. scalar mss       = 1.68

. scalar F         = 21

. scalar rss       = 1.8

. scalar r2        = 4.82758620689655E-01

. scalar rmse      = 0.1

. 
. qui input byte treat double resp

. 
. anova resp treat

                           Number of obs =     189     R-squared     =  0.4828
                           Root MSE      =      .1     Adj R-squared =  0.4598

                  Source |  Partial SS    df       MS           F     Prob > F
              -----------+----------------------------------------------------
                   Model |        1.68     8         .21      21.00     0.0000
                         |
                   treat |        1.68     8         .21      21.00     0.0000
                         |
                Residual |         1.8   180         .01   
              -----------+----------------------------------------------------
                   Total |        3.48   188  .018510638   

. 
. 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)                14.9
e(rmse)             15.2
e(r2)               15.3
e(mss)              15.6
e(rss)              14.8

. 
end of do-file