How to draw a residual plot after xtreg, re command

[sophie maene]

Dear Statalist,

I am running a random effects model and would love to draw a residual plot of predicted vs. fitted values for my analysis.

streng c.age##c.age##i.LTCsystem, re vce(cluster mergeid_n)
rvfplot, yline(0)
rvfplot2

Nevertheless, the rvfplot command and rvfplot2 are not working. For rvfplot I receive the error: last estimates not found r(301) and for the rvfplot2 I receive the error: option residuals not allowed
r(198).

I have already looked into other with the same problem, but then rvfplot2 came up as a solution, which is not working with me.

Thank you!

[Carlo Lazzaro]

Sophie:
do you mean something along the following lines?

. use "https://www.stata-press.com/data/r16/nlswork.dta"
(National Longitudinal Survey.  Young Women 14-26 years of age in 1968)

. xtreg ln_wage age i.race

Random-effects GLS regression                   Number of obs     =     28,510
Group variable: idcode                          Number of groups  =      4,710

R-sq:                                           Obs per group:
     within  = 0.1026                                         min =          1
     between = 0.1032                                         avg =        6.1
     overall = 0.0945                                         max =         15

                                                Wald chi2(3)      =    3242.34
corr(u_i, X)   = 0 (assumed)                    Prob > chi2       =     0.0000

------------------------------------------------------------------------------
     ln_wage |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         age |    .018534    .000331    55.99   0.000     .0178852    .0191828
             |
        race |
      black  |  -.1209428   .0129079    -9.37   0.000    -.1462418   -.0956439
      other  |   .0981941   .0538424     1.82   0.068    -.0073351    .2037233
             |
       _cons |    1.15423   .0118069    97.76   0.000     1.131089    1.177371
-------------+----------------------------------------------------------------
     sigma_u |  .36581626
     sigma_e |  .30349389
         rho |  .59231394   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. predict Fitted, xb
(24 missing values generated)

. predict Epsilon, e
(24 missing values generated)

. twoway (scatter Epsilon Fitted), ytitle(Epsilon residuals) xtitle(Fitted values)

[sophie maene]

Yes, thank you very much for the help!