Germán Rodríguez
Multilevel Models Princeton University

Using MLwiN's Command Interface

In class we have illustrated the use of MLwiN using the Graphical User Interface (GUI). For serious work you should (1) log the results, and (2) use the Command Interface so you can store all your commands on a file and ensure that you can reproduce your results at a later time. The online help has a useful section on Using the command interface. Here are some hints.

Log File

The command logo filename logs the results on a file. You can turn this feature on using logo 1 and off using logo 0. You must use the last command to ensure that the log file is closed properly.

To log commands as well as results turn echo on using echo 1. Note that if you read data and echo is on the entire dataset will be listed. For best results set echo 0 before reading data and echo 1 afterwards.

Reading Data

Here's how to read the data from Snijders and Bosker (1999), henceforth SB, that we have been using in class. Make sure you use the correct local or network filename. I also use put to generate a vector of ones and name to assign variable names.

It is usually a good idea to compute means or other summary statistics to ensure you read the data OK.

echo 0
dinput c1-c4
d:\pop510\snijders4.dat
echo 1
put 2287 1 c5
name c1 "school" c2 "pupil" c3 "iqverb" c4 "langpost" c5 "one"

Variance Components

Here's how to define the level id's and the response variable, and how to fit a simple variance components model with constant variation at levels 1 and 2. All explanatory variables must be declared using expl and are automatically added to the fixed part. The random structure is declared using setv. I use settings to ensure all is well.

iden 1 "pupil" 2 "school"
response "langpost"
explanatory 1 "one"
setv 1 "one"
setv 2 "one"
settings

The feedback of the last command is shown below:

settings 
EXPLanatory variables in       one      
FPARameters                    one      
RESPonse variable in           langpost 
FSDErrors : uncorrected                 RSDErrors : uncorrected
MAXIterations  20   TOLErance     2     METHod is IGLS    BATCh is OFF
IDENtifying codes : 1-pupil, 2-school
 
LEVEL 2 RPM
         one      
one      1        
LEVEL 1 RPM(RESETTING OFF)
         one      
one      1      

To fit a model using a macro file you must set batch mode on using bath 1, otherwise you get only one iteration. To list results use fixed and random.

batch 1
start
fixed
random

The output is shown below, with commands in bold.

batch 1 
 
Batch mode is ON
start 
 
Convergence achieved
fixed 
 
 
  PARAMETER            ESTIMATE     S. ERROR(U)   PREV. ESTIMATE
one                       40.36       0.4263              40.36 
random 
LEV.  PARAMETER       (NCONV)    ESTIMATE    S. ERROR(U)  PREV. ESTIM     CORR.
-------------------------------------------------------------------------------
 2    one      /one      ( 1)       19.42          2.921        19.34         1
-------------------------------------------------------------------------------
 1    one      /one      ( 2)       64.57          1.967        64.58 

These are the results in SB-Table 4.1.

Random Intercepts

To fit a random-intercept model we use expl 1 to add an explanatory variable:

expl 1 "iqverb"
start
fixed
random

This is the output, again with commands in bold:

expl 1 "iqverb" 
start 
 
Convergence achieved
fixed 
 
 
  PARAMETER            ESTIMATE     S. ERROR(U)   PREV. ESTIMATE
one                       11.17       0.8788              11.16 
iqverb                    2.488      0.07005              2.488 
random 
LEV.  PARAMETER       (NCONV)    ESTIMATE    S. ERROR(U)  PREV. ESTIM     CORR.
-------------------------------------------------------------------------------
 2    one      /one      ( 1)       9.496          1.515        9.486         1
-------------------------------------------------------------------------------
 1    one      /one      ( 2)       42.23          1.286        42.23 

This is the parallel lines model in SB-Table 4.2.

Random Slopes

To make the slope of verbal IQ random at the school level we use setv specifying the level and variable name. I also use like to print the likelihood

setv 2 "iqverb"
start
fixed
random

Here's the output

setv 2 "iqverb" 
start 
 
Convergence achieved
fixed 
 
 
  PARAMETER            ESTIMATE     S. ERROR(U)   PREV. ESTIMATE
one                       10.81        1.111              10.81 
iqverb                    2.526      0.08145              2.526 
random 
LEV.  PARAMETER       (NCONV)    ESTIMATE    S. ERROR(U)  PREV. ESTIM     CORR.
-------------------------------------------------------------------------------
 2    one      /one      ( 2)       65.86             19        65.82         1
 2    iqverb   /one      ( 1)       -3.63          1.352       -3.628    -0.976
 2    iqverb   /iqverb   ( 1)        0.21        0.09914       0.2099         1
-------------------------------------------------------------------------------
 1    one      /one      ( 3)       41.48          1.291        41.48 
likelihood 
979232 spaces left on worksheet
 
-2*log(lh) is      15230.8

The same results in the equation window look like this: