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name: <unnamed>
log: Q:\C-modelling\runmlwin\website\logfiles\2024-10-11\18\7.4.smcl
log type: smcl
opened on: 11 Oct 2024, 18:41:07
. ****************************************************************************
. * Module 7: Multilevel Models for Binary Responses Stata Practicals
. *
. * P7.4: Predicted Probabilities from a Multilevel 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/7.4.dta", clear
.
. runmlwin antemed cons magec magecsq meduc2 meduc3 wealthc, ///
> level2(comm: cons) ///
> level1(womid:) ///
> discrete(distribution(binomial) link(logit) denominator(cons) pql2) /
> //
> nopause
MLwiN 3.13 multilevel model Number of obs = 5366
Binomial logit response model (hierarchical)
Estimation algorithm: IGLS, PQL2
-----------------------------------------------------------
| No. of Observations per Group
Level Variable | Groups Minimum Average Maximum
----------------+------------------------------------------
comm | 361 3 14.9 25
-----------------------------------------------------------
Run time (seconds) = 3.44
Number of iterations = 5
------------------------------------------------------------------------------
antemed | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
cons | -.4546834 .0827282 -5.50 0.000 -.6168277 -.2925392
magec | -.0003881 .006554 -0.06 0.953 -.0132337 .0124574
magecsq | -.0010068 .0006828 -1.47 0.140 -.002345 .0003314
meduc2 | .5478987 .0845976 6.48 0.000 .3820905 .7137069
meduc3 | 1.309241 .0977836 13.39 0.000 1.117589 1.500893
wealthc | .3977514 .029586 13.44 0.000 .3397638 .4557389
------------------------------------------------------------------------------
------------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf. Interval]
-----------------------------+------------------------------------------------
Level 2: comm |
var(cons) | .8538518 .0935791 .6704402 1.037263
------------------------------------------------------------------------------
.
. replace magec = 0
(5,366 real changes made)
.
. replace magecsq = 0
(5,366 real changes made)
.
. predict predxb
.
. generate medianpredprob = invlogit(predxb)
.
. egen pickone = tag(wealth meduc)
.
. sort wealth meduc
.
. list wealth meduc medianpredprob if pickone==1, abbreviate(14) sepby(wealth)
+---------------------------------+
| wealth meduc medianpredprob |
|---------------------------------|
543. | 1 1 .2221039 |
973. | 1 2 .3305831 |
1135. | 1 3 .5139447 |
|---------------------------------|
1491. | 2 1 .2982393 |
1685. | 2 2 .4236524 |
2121. | 2 3 .6114817 |
|---------------------------------|
2221. | 3 1 .3874735 |
2689. | 3 2 .5224733 |
2964. | 3 3 .700839 |
|---------------------------------|
3253. | 4 1 .4849561 |
3613. | 4 2 .6195657 |
3939. | 4 3 .777135 |
|---------------------------------|
4186. | 5 1 .5835972 |
4514. | 5 2 .7079517 |
4845. | 5 3 .8384579 |
+---------------------------------+
.
. generate medianpredlogit = logit(medianpredprob)
.
. keep if pickone==1
(5,351 observations deleted)
.
. keep wealth meduc medianpredprob medianpredlogit
.
. list, abbreviate(15) sepby(wealth)
+---------------------------------------------------+
| meduc wealth medianpredprob medianpredlogit |
|---------------------------------------------------|
1. | 1 1 .2221039 -1.253448 |
2. | 2 1 .3305831 -.7055489 |
3. | 3 1 .5139447 .0557934 |
|---------------------------------------------------|
4. | 1 2 .2982393 -.8556963 |
5. | 2 2 .4236524 -.3077976 |
6. | 3 2 .6114817 .4535449 |
|---------------------------------------------------|
7. | 1 3 .3874735 -.4579449 |
8. | 2 3 .5224733 .0899537 |
9. | 3 3 .700839 .8512962 |
|---------------------------------------------------|
10. | 1 4 .4849561 -.0601936 |
11. | 2 4 .6195657 .4877051 |
12. | 3 4 .777135 1.249048 |
|---------------------------------------------------|
13. | 1 5 .5835972 .3375579 |
14. | 2 5 .7079517 .8854565 |
15. | 3 5 .8384579 1.646799 |
+---------------------------------------------------+
.
. expand 1000
(14,985 observations created)
.
. generate u = rnormal(0,sqrt(0.889))
.
. generate meanpredprob = invlogit(medianpredlogit + u)
.
. collapse (mean) meanpredprob, by(wealth meduc medianpredprob)
.
. list wealth meduc medianpredprob meanpredprob, abbreviate(14) sepby(wealth)
+------------------------------------------------+
| wealth meduc medianpredprob meanpredprob |
|------------------------------------------------|
1. | 1 1 .2221039 .2607134 |
2. | 1 2 .3305831 .351727 |
3. | 1 3 .5139447 .5015319 |
|------------------------------------------------|
4. | 2 1 .2982393 .3314112 |
5. | 2 2 .4236524 .4415864 |
6. | 2 3 .6114817 .5943345 |
|------------------------------------------------|
7. | 3 1 .3874735 .4119753 |
8. | 3 2 .5224733 .5235564 |
9. | 3 3 .700839 .6627779 |
|------------------------------------------------|
10. | 4 1 .4849561 .497875 |
11. | 4 2 .6195657 .59526 |
12. | 4 3 .777135 .7437027 |
|------------------------------------------------|
13. | 5 1 .5835972 .5741999 |
14. | 5 2 .7079517 .6912331 |
15. | 5 3 .8384579 .8028967 |
+------------------------------------------------+
.
end of do-file