-------------------------------------------------------------------------------
      name:  <unnamed>
       log:  Q:\C-modelling\runmlwin\website\logfiles\2020-03-27\16\6.2.smcl
  log type:  smcl
 opened on:  27 Mar 2020, 18:21:50

. ****************************************************************************
. * Module 6: Regression Models for Binary Responses Stata Practicals
. *
. *     P6.2: Moving Towards a Regression Model: The Linear Probability Model
. *
. *           George Leckie
. *           Centre for Multilevel Modelling, 2010
. ****************************************************************************
. *     Stata do-file to replicate all analyses using runmlwin
. *
. *     George Leckie
. *     Centre for Multilevel Modelling, 2013
. *     http://www.bristol.ac.uk/cmm/software/runmlwin/
. ****************************************************************************
. 
. use "http://www.bristol.ac.uk/cmm/media/runmlwin/6.2.dta", clear

. 
. generate meduc2 = meduc==2

. 
. generate meduc3 = meduc==3

. 
. summarize mage

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
        mage |      5,366    23.63436     6.26707         13         49

. 
. generate magec = mage - 23.634

. 
. generate magecsq = magec * magec

. 
. runmlwin antemed cons magec magecsq urban meduc2 meduc3, ///
>         level1(womid: cons, residuals(estd)) ///
>         nopause
 
MLwiN 3.05 multilevel model                     Number of obs      =      5366
Normal response model (hierarchical)
Estimation algorithm: IGLS

Run time (seconds)   =       0.64
Number of iterations =          2
Log likelihood       = -3362.1113
Deviance             =  6724.2226
------------------------------------------------------------------------------
     antemed |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        cons |   .2718846   .0122729   22.15    0.000     .2478301     .295939
       magec |   .0017867   .0011931    1.50    0.134    -.0005517    .0041251
     magecsq |  -.0004067   .0001239   -3.28    0.001    -.0006496   -.0001639
       urban |   .2501874   .0134618   18.59    0.000     .2238029     .276572
      meduc2 |   .1516849   .0155997    9.72    0.000       .12111    .1822598
      meduc3 |   .3826707   .0156629   24.43    0.000      .351972    .4133695
------------------------------------------------------------------------------

------------------------------------------------------------------------------
   Random-effects Parameters |   Estimate   Std. Err.     [95% Conf. Interval]
-----------------------------+------------------------------------------------
Level 1: womid               |
                   var(cons) |   .2049968   .0039576        .19724    .2127537
------------------------------------------------------------------------------

. 
. preserve

. 
.         summarize urban

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
       urban |      5,366    .3138278    .4640906          0          1

. 
.         replace urban = 0.314
variable urban was byte now float
(5,366 real changes made)

. 
.         summarize meduc2

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
      meduc2 |      5,366    .3073053      .46142          0          1

. 
.         replace meduc2 = 0.307
(5,366 real changes made)

. 
.         summarize meduc3

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
      meduc3 |      5,366    .3449497    .4753962          0          1

. 
.         replace meduc3 = 0.345
(5,366 real changes made)

. 
.         predict predantemed

. 
.         line predantemed mage if inrange(mage,15,45)

. 
.         line predantemed mage if inrange(mage,15,45), sort

. 
. restore

. 
. predict predprob

. 
. scatter estd0 predprob

. 
end of do-file