version 13.1
clear
// Data set for Example 16.1
// mlbook2, data set with pupils having missings on ses or IQ_verb or (langPOST and aritPOST) excluded.
input schoolnr pupilNR_new langPOST aritPOST ses IQ_verb IQ_perf Minority denomina sch_ses sch_iqv sch_min
1.00 1.00 . 12.00 -17.73 -1.37 -3.75 1.00 1.00 -14.035 -1.4039 0.630
1.00 3.00 46.00 24.00 -4.73 3.13 1.25 0.00 1.00 -14.035 -1.4039 0.630
1.00 4.00 45.00 19.00 -17.73 2.63 -1.08 1.00 1.00 -14.035 -1.4039 0.630
1.00 5.00 33.00 24.00 -12.73 -2.37 -0.08 0.00 1.00 -14.035 -1.4039 0.630
1.00 6.00 46.00 26.00 -4.73 -0.87 -1.08 0.00 1.00 -14.035 -1.4039 0.630
1.00 7.00 20.00 9.00 -17.73 -3.87 -4.41 0.00 1.00 -14.035 -1.4039 0.630
1.00 8.00 30.00 13.00 -17.73 -2.37 -2.08 1.00 1.00 -14.035 -1.4039 0.630
// .. Skip a few cases ..
end
// 1. State Mlwin path:
global MLwiN_path C:\Program Files (x86)\MLwiN v2.31\i386\mlwin.exe
// 2. Create constant for models:
generate cons = 1
// 3. Fit models:
// Results of Table 16.1:
runmlwin (langPOST cons, eq(1)) (aritPOST cons, eq(2)), ///
level2(schoolnr: (cons, eq(1)) (cons, eq(2))) ///
level1(pupilNR_new: (cons, eq(1)) (cons, eq(2))) ///
nopause
// Population correlation coefficients:
di [RP2]cov(cons_1\cons_2) / sqrt([RP2]var(cons_1)*[RP2]var(cons_2)) // School-level
di [RP1]cov(cons_1\cons_2) / sqrt([RP1]var(cons_1)*[RP1]var(cons_2)) // Student-level
// This one seems a bit off in the book:
di ([RP2]cov(cons_1\cons_2) + [RP1]cov(cons_1\cons_2)) / sqrt( ([RP2]var(cons_1) + [RP1]var(cons_1)) ///
* ([RP2]var(cons_2) + [RP1]var(cons_2)))
// Correlation between group means for groups of a hypothetical size n = 30
di ([RP2]cov(cons_1\cons_2) + [RP1]cov(cons_1\cons_2) /30) / sqrt( ([RP2]var(cons_1) + [RP1]var(cons_1) /30) ///
* ([RP2]var(cons_2) + [RP1]var(cons_2) /30))
// Results of Table 16.2:
// - Create interaction terms (-runmlwin- doesn't accept factor variables):
generate iqXses = IQ_verb * ses
generate schiqXschses = sch_iqv * sch_ses
// - Fit model:
runmlwin (langPOST cons IQ_verb ses sch_iqv sch_ses iqXses schiqXschses, eq(1)) ///
(aritPOST cons IQ_verb ses sch_iqv sch_ses iqXses schiqXschses, eq(2)), ///
level2(schoolnr: (cons, eq(1)) (cons, eq(2))) ///
level1(pupilNR_new: (cons, eq(1)) (cons, eq(2))) ///
nopause
References
Leckie, George, and Chris Charlton. 2013. "runmlwin. A Program to Run the MLwiN Multilevel Modeling Software from within Stata." Journal of Statistical Software 52(11):1-40.Snijders, Tom, and Roel Boskers. 2012. Multilevel Analysis. An Introduction to Basic and Advanced Multilevel Modeling, 2nd ed. Sage.
