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Error message: ...Constraint matrix is invalid...
Posted: Tue Nov 22, 2011 10:55 pm
by michaellawton
Hello
I had a multilevel growth curve model programed in runmlwin on my desktop using MLwiN 2.23. The program included constraints such as:
constraint define 1 [RP2]var(cons) = 0.259
constraint define 2 ...
runmlwin ... constraint(1/4)
The program worked fine, however I am now trying to run the same program on a laptop using MLwiN 2.24 and I get the following error message
"Row 1 of the constraint matrix is invalid as it involves both fixed part and random part parameters"
Any help on how to fix this would be greatly appreciated. Many thanks, Michael
Re: Error message: ...Constraint matrix is invalid...
Posted: Wed Nov 23, 2011 6:49 pm
by GeorgeLeckie
Hi Michael,
In the latest release of runmlwin we made runmlwin backwards compatible with Stata versions 9 and 10. However, a bug crept in relating to the constraints.
We have now fixed the bug for the next SSC release.
Michael, I will email you the fix. If anyone else would like the fix then please contact me by replying to this post.
Below is a rather contrived example where we constrain the the random part parameters of a linear growth curve model to be specific values. The example shows what the runmlwin output should look like after you have applied the fix.
Code: Select all
. use "http://www.stata-press.com/data/mlmus2/asian.dta", clear
.
. gen cons = 1
.
. gen age2 = age^2
.
. runmlwin weight cons age age2, ///
> level2(id: cons age) ///
> level1(occ: cons) ///
> nopause
MLwiN 2.24 multilevel model Number of obs = 198
Normal response model
Estimation algorithm: IGLS
-----------------------------------------------------------
| No. of Observations per Group
Level Variable | Groups Minimum Average Maximum
----------------+------------------------------------------
id | 68 1 2.9 5
-----------------------------------------------------------
Run time (seconds) = 1.58
Number of iterations = 7
Log likelihood = -258.07785
Deviance = 516.1557
------------------------------------------------------------------------------
weight | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
cons | 3.494518 .1372489 25.46 0.000 3.225515 3.76352
age | 7.704002 .2394275 32.18 0.000 7.234733 8.173271
age2 | -1.660475 .0885319 -18.76 0.000 -1.833994 -1.486955
------------------------------------------------------------------------------
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
Level 2: id |
var(cons) | .4040045 .1412488 .1271619 .6808471
cov(cons,age) | .088273 .0812774 -.0710279 .2475738
var(age) | .2539857 .0858503 .0857222 .4222493
-----------------------------+------------------------------------------------
Level 1: occ |
var(cons) | .331641 .0532307 .2273107 .4359712
------------------------------------------------------------------------------
.
. constraint define 1 [RP2]var(cons) = 0.5
. constraint define 2 [RP2]cov(cons\age) = 0.1
. constraint define 3 [RP2]var(age) = 0.25
. constraint define 4 [RP1]var(cons) = 0.3
.
. runmlwin weight cons age age2, ///
> level2(id: cons age) ///
> level1(occ: cons) ///
> constraints(1/4) nopause
( 1) [RP2]var(cons) = .5
( 2) [RP2]cov(cons\age) = .1
( 3) [RP2]var(age) = .25
( 4) [RP1]var(cons) = .3
MLwiN 2.24 multilevel model Number of obs = 198
Normal response model
Estimation algorithm: IGLS
-----------------------------------------------------------
| No. of Observations per Group
Level Variable | Groups Minimum Average Maximum
----------------+------------------------------------------
id | 68 1 2.9 5
-----------------------------------------------------------
Run time (seconds) = 1.37
Number of iterations = 2
Log likelihood = -258.49789
Deviance = 516.99579
------------------------------------------------------------------------------
weight | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
cons | 3.489141 .1388873 25.12 0.000 3.216926 3.761355
age | 7.713635 .2307907 33.42 0.000 7.261294 8.165977
age2 | -1.663078 .0850955 -19.54 0.000 -1.829862 -1.496294
------------------------------------------------------------------------------
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
Level 2: id |
var(cons) | .5 6.32e-09 .5 .5
cov(cons,age) | .1 2.85e-09 .1 .1
var(age) | .25 1.64e-09 .25 .25
-----------------------------+------------------------------------------------
Level 1: occ |
var(cons) | .3 6.37e-09 .3 .3
------------------------------------------------------------------------------
Best wishes
George