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name: <unnamed>
log: Q:\C-modelling\runmlwin\website\logfiles\2024-10-11\18\11.2.smcl
log type: smcl
opened on: 11 Oct 2024, 18:42:14
. ****************************************************************************
. * Module 11: Three and Higher-Level Models - Stata Practical
. *
. * P11.2: A Three-Level Model of THKS
. *
. * George Leckie
. * Centre for Multilevel Modelling, 2011
. ****************************************************************************
. * Stata do-file to replicate all analyses using runmlwin
. *
. * George Leckie
. * Centre for Multilevel Modelling, 2013
. * http://www.bristol.ac.uk/cmm/software/runmlwin/
. ****************************************************************************
.
. * P11.2.1 Specifying and fitting the three-level model
.
. use "http://www.bristol.ac.uk/cmm/media/runmlwin/11.2.dta", clear
.
. runmlwin postthks cons, ///
> level3(schoolid: cons, residuals(v)) ///
> level2(classid: cons, residuals(u)) ///
> level1(studentid: cons) ///
> nopause
MLwiN 3.13 multilevel model Number of obs = 1600
Normal response model (hierarchical)
Estimation algorithm: IGLS
-----------------------------------------------------------
| No. of Observations per Group
Level Variable | Groups Minimum Average Maximum
----------------+------------------------------------------
schoolid | 28 18 57.1 137
classid | 135 1 11.9 28
-----------------------------------------------------------
Run time (seconds) = 3.21
Number of iterations = 4
Log likelihood = -2750.9908
Deviance = 5501.9816
------------------------------------------------------------------------------
postthks | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
cons | 2.663487 .0781224 34.09 0.000 2.51037 2.816604
------------------------------------------------------------------------------
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
Level 3: schoolid |
var(cons) | .1103113 .0457034 .0207343 .1998884
-----------------------------+------------------------------------------------
Level 2: classid |
var(cons) | .0848017 .0327901 .0205343 .149069
-----------------------------+------------------------------------------------
Level 1: studentid |
var(cons) | 1.723674 .0634102 1.599392 1.847955
------------------------------------------------------------------------------
.
. estimates store model1
.
.
.
. * P11.2.2 Interpretation of the three-level mode;
.
.
.
. * P11.2.3 Calculating variance partition coefficients (VPCs) and intraclass
. * correlations (ICCs)
.
.
.
. * P11.2.4 Predicting and examining school and classroom effects
.
. egen v0rank = rank(v0) if pickone_school==1
(1,572 missing values generated)
.
. egen u0rank = rank(u0) if pickone_class==1
(1,465 missing values generated)
.
. sort v0rank
.
. list schoolid v0 v0se v0rank if pickone_school==1, noobs
+------------------------------------------+
| schoolid v0 v0se v0rank |
|------------------------------------------|
| 506 -.536879 .1732999 1 |
| 513 -.4589806 .2171219 2 |
| 515 -.3405864 .1453007 3 |
| 507 -.3385126 .177263 4 |
| 410 -.3382328 .2159964 5 |
|------------------------------------------|
| 199 -.334378 .1931299 6 |
| 194 -.1455744 .1792061 7 |
| 409 -.1397455 .1847486 8 |
| 197 -.1182113 .2132904 9 |
| 405 -.1078893 .20518 10 |
|------------------------------------------|
| 402 -.0978065 .2295873 11 |
| 505 -.0724921 .1751819 12 |
| 198 -.071732 .20518 13 |
| 193 -.0689895 .2546527 14 |
| 412 .0325697 .2094178 15 |
|------------------------------------------|
| 509 .0463831 .1597266 16 |
| 404 .0669768 .2321721 17 |
| 408 .0866747 .2293949 18 |
| 407 .1607906 .198829 19 |
| 514 .2152646 .1667683 20 |
|------------------------------------------|
| 414 .25143 .2077815 21 |
| 411 .2679052 .2506294 22 |
| 401 .2747781 .2246474 23 |
| 196 .2877176 .233327 24 |
| 510 .3139966 .1616469 25 |
|------------------------------------------|
| 508 .3199214 .1837873 26 |
| 403 .3595921 .2491774 27 |
| 415 .4860094 .1853557 28 |
+------------------------------------------+
.
. summarize u0 if pickone_class==1
Variable | Obs Mean Std. dev. Min Max
-------------+---------------------------------------------------------
u0 | 135 4.88e-17 .1583189 -.4351861 .4740873
.
. qnorm v0 if pickone_school==1, aspectratio(1)
.
. qnorm u0 if pickone_class==1, aspectratio(1)
.
. generate labheight = v0 + 1.96*v0se + 0.05
.
. serrbar v0 v0se v0rank if pickone_school==1, scale(1.96) yline(0) ///
> addplot(scatter labheight v0rank, ///
> msymbol(none) mlabel(schoolid) ///
> mlabposition(1) mlabangle(vertical) mlabcolor(navy)) ///
> ytitle("Predicted school effect") xtitle("Rank") ///
> legend(off)
.
. serrbar u0 u0se u0rank if pickone_class==1, scale(1.96) yline(0) ///
> ytitle("Predicted classroom effect") xtitle("Rank")
.
. count if ((u0 + 1.96*u0se)<0 | (u0 - 1.96*u0se)>0) & pickone_class==1
1
.
end of do-file