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       log:  Q:\C-modelling\runmlwin\website\logfiles\2020-03-27\16\3_Residuals
> .smcl
  log type:  smcl
 opened on:  27 Mar 2020, 17:41:40

. ****************************************************************************
. *     MLwiN User Manual 
. *
. * 3   Residuals                                                           37
. *
. *     Rasbash, J., Steele, F., Browne, W. J. and Goldstein, H. (2012).
. *     A User’s Guide to MLwiN, v2.26. Centre for Multilevel Modelling,
. *     University of Bristol.
. ****************************************************************************
. *     Stata do-file to replicate all analyses using runmlwin
. *
. *     George Leckie and Chris Charlton, 
. *     Centre for Multilevel Modelling, 2012
. *     http://www.bristol.ac.uk/cmm/software/runmlwin/
. ****************************************************************************
. 
. * 3.1 What are multilevel residuals? . . . . . . . . . . . . . . . . . . .37
. 
. use "http://www.bristol.ac.uk/cmm/media/runmlwin/tutorial.dta", clear

. 
. runmlwin normexam cons, ///
>         level2(school: cons, residuals(u)) ///
>         level1(student: cons, residuals(e)) ///
>         nopause
 
MLwiN 3.05 multilevel model                     Number of obs      =      4059
Normal response model (hierarchical)
Estimation algorithm: IGLS

-----------------------------------------------------------
                |   No. of       Observations per Group
 Level Variable |   Groups    Minimum    Average    Maximum
----------------+------------------------------------------
         school |       65          2       62.4        198
-----------------------------------------------------------

Run time (seconds)   =       0.72
Number of iterations =          3
Log likelihood       =  -5505.324
Deviance             =  11010.648
------------------------------------------------------------------------------
    normexam |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        cons |  -.0131668   .0536254   -0.25    0.806    -.1182706     .091937
------------------------------------------------------------------------------

------------------------------------------------------------------------------
   Random-effects Parameters |   Estimate   Std. Err.     [95% Conf. Interval]
-----------------------------+------------------------------------------------
Level 2: school              |
                   var(cons) |    .168625   .0324466      .1050308    .2322193
-----------------------------+------------------------------------------------
Level 1: student             |
                   var(cons) |   .8477613   .0189712      .8105785    .8849441
------------------------------------------------------------------------------

. 
. 
. 
. * 3.2 Calculating residuals in MLwiN . . . . . . . . . . . . . . . . . . .40
. 
. egen pickone = tag(school)

. 
. egen u0rank = rank(u0) if pickone==1
(3994 missing values generated)

. 
. serrbar u0 u0se u0rank if pickone==1, scale(1.96) yline(0)

. 
. 
. 
. * 3.3 Normal plots . . . . . . . . . . . . . . . . . . . . . . . . . . . .43
. 
. summarize e0

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
          e0 |      4,059   -3.31e-18    .9141767  -3.634258   3.367905

. 
. generate e0std = (e0 - r(mean))/r(sd)

. 
. egen e0rank = rank(e0)

. 
. generate e0uniform = (e0rank - 0.5)/_N

. 
. generate e0nscore = invnorm(e0uniform)

. 
. scatter e0std e0nscore, ///
>         yline(0) xline(0) ylabel(-4(1)4) xlabel(-4(1)4) aspectratio(1)

. 
. keep if pickone==1
(3,994 observations deleted)

. 
. keep u0 u0rank

. 
. summarize u0

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
          u0 |         65    3.25e-17    .3930771  -.9358178   .9485863

. 
. generate u0std = (u0 - r(mean))/r(sd)

. 
. generate u0uniform = (u0rank - 0.5)/_N

. 
. generate u0nscore = invnorm(u0uniform)

. 
. scatter u0std u0nscore, ///
>         yline(0) xline(0) ylabel(-3(1)3) xlabel(-3(1)3) aspectratio(1)

. 
. save "tutorial3.dta", replace
file tutorial3.dta saved

. 
. 
. 
. * Chapter learning outcomes . . . . . . . . . . . . . . . . . . . . . . . 45
. 
. 
. 
. ****************************************************************************
. exit

end of do-file