Dear all,
I’m running three different commands in SAS that should give me the same results, where the cluster ID is branch
Command 1 and Command 2 give me the same result
However, Command 3, which should give me the same result does not.
Can someone please explain why Command 2 does not give me the same results as Command 3?
For Command 1 and Command 2,
The coefficeints on support and satis are 0.7139836 and 0.5490609 respectively
However for Command 3, ...
The coefficeints on support and satis are 0.6981603 and 0.6042986 respectively
Is the reason possible because command 3 uses random effects and command 2 uses fixed effects?
support .7139836 .0251594 28.38 0.000 .6646302 .7633371
satis .5490609
Variables include:
branch [large department store in 75 locations | cluster variable or group variable]
perform (Y variable) job performance [from 1500 employees]
satis (M variable) job satisfaction [from 1500 employees]
support (X variable) perceived support from managers
Command 1: Using xtreg
use https://www.stata-press.com/data/r18/gsem_multmed
xtset branch
xtreg perform support satis, fe
Command 2: Using gsem
use https://www.stata-press.com/data/r18/gsem_multmed
gsem (perform<-support satis i.branch L, regress)
Command 3: Using gsem
use https://www.stata-press.com/data/r18/gsem_multmed
gsem (perform<-support satis M1[branch] L, regress)
Any help would be really appreciated here?
The results from all 3 commands are below.
. do "C:\Users\rseg6065\AppData\Local\Temp\STD77e4_0000 00.tmp"
. use https://www.stata-press.com/data/r18/gsem_multmed
(Fictional job-performance data)
. xtset branch
Panel variable: branch (balanced)
. xtreg perform support satis, fe
Fixed-effects (within) regression Number of obs = 1,500
Group variable: branch Number of groups = 75
R-squared: Obs per group:
Within = 0.5317 min = 20
Between = 0.6588 avg = 20.0
Overall = 0.5392 max = 20
F(2,1423) = 807.74
corr(u_i, Xb) = 0.2744 Prob > F = 0.0000
perform Coefficient Std. err. t P>t [95% conf. interval]
support .7139836 .0251594 28.38 0.000 .6646302 .7633371
satis .5490609 .0344488 15.94 0.000 .4814851 .6166367
_cons 4.987632 .0115951 430.15 0.000 4.964887 5.010377
sigma_u .4419321
sigma_e .44829979
rho .49284752 (fraction of variance due to u_i)
F test that all u_i=0: F(74, 1423) = 15.03 Prob > F = 0.0000
.
end of do-file
. do "C:\Users\rseg6065\AppData\Local\Temp\STD77e4_0000 00.tmp"
. use https://www.stata-press.com/data/r18/gsem_multmed
(Fictional job-performance data)
. gsem (perform<-support satis i.branch L, regress)
Fitting fixed-effects model:
Iteration 0: log likelihood = -885.44481
Iteration 1: log likelihood = -885.44481
Refining starting values:
Grid node 0: log likelihood = -1629.4487
Fitting full model:
Iteration 0: log likelihood = -1629.4487 (not concave)
Iteration 1: log likelihood = -1486.8896 (not concave)
Iteration 2: log likelihood = -1425.1065 (not concave)
Iteration 3: log likelihood = -1401.0718 (not concave)
Iteration 4: log likelihood = -1398.7055 (not concave)
Iteration 5: log likelihood = -1396.8134 (not concave)
Iteration 6: log likelihood = -1396.4355 (not concave)
Iteration 7: log likelihood = -1396.3599 (not concave)
Iteration 8: log likelihood = -1396.3523 (not concave)
Iteration 9: log likelihood = -1396.3463 (not concave)
Iteration 10: log likelihood = -1396.346 (not concave)
Iteration 11: log likelihood = -1396.3457 (not concave)
Iteration 12: log likelihood = -1396.3457 (not concave)
Iteration 13: log likelihood = -1396.3457 (not concave)
Iteration 14: log likelihood = -1396.3457 (not concave)
Iteration 15: log likelihood = -1396.3457 (not concave)
Iteration 16: log likelihood = -1396.3457 (not concave)
Iteration 17: log likelihood = -1396.3457 (not concave)
Iteration 18: log likelihood = -1396.3457 (not concave)
Iteration 19: log likelihood = -1396.3457 (not concave)
Iteration 20: log likelihood = -1396.3457 (not concave)
Iteration 21: log likelihood = -1396.3457 (not concave)
Iteration 22: log likelihood = -1396.3457 (not concave)
Iteration 23: log likelihood = -1396.3457 (not concave)
Iteration 24: log likelihood = -1396.3457 (not concave)
Iteration 25: log likelihood = -1396.3457 (not concave)
Iteration 26: log likelihood = -1396.3457 (not concave)
Iteration 27: log likelihood = -1396.3457 (not concave)
Iteration 28: log likelihood = -1396.3457 (not concave)
Iteration 29: log likelihood = -1396.3457 (not concave)
Iteration 30: log likelihood = -1396.3457 (not concave)
Iteration 31: log likelihood = -1396.3457 (not concave)
Iteration 32: log likelihood = -1396.3457 (not concave)
Iteration 33: log likelihood = -1396.3454 (not concave)
Iteration 34: log likelihood = -1396.3454 (not concave)
Iteration 35: log likelihood = -1396.3436 (not concave)
Iteration 36: log likelihood = -1396.3436 (not concave)
Iteration 37: log likelihood = -1396.3434 (not concave)
Iteration 38: log likelihood = -1396.3291 (not concave)
Iteration 39: log likelihood = -1396.3277 (not concave)
Iteration 40: log likelihood = -1396.2545 (not concave)
Iteration 41: log likelihood = -1396.1374 (not concave)
Iteration 42: log likelihood = -1395.9499 (not concave)
Iteration 43: log likelihood = -1395.9125 (not concave)
Iteration 44: log likelihood = -1394.9524 (not concave)
Iteration 45: log likelihood = -1394.5685 (not concave)
Iteration 46: log likelihood = -1393.3396 (not concave)
Iteration 47: log likelihood = -1393.2782 (not concave)
Iteration 48: log likelihood = -1391.7052 (not concave)
Iteration 49: log likelihood = -1391.0764 (not concave)
Iteration 50: log likelihood = -1382.9928 (not concave)
Iteration 51: log likelihood = -892.31152
Iteration 52: log likelihood = -886.52405 (not concave)
Iteration 53: log likelihood = -885.44561 (not concave)
Iteration 54: log likelihood = -885.44481 (not concave)
Iteration 55: log likelihood = -885.44481 (not concave)
Iteration 56: log likelihood = -885.44481 (not concave)
Iteration 57: log likelihood = -885.44481 (backed up)
Generalized structural equation model Number of obs = 1,500
Response: perform
Family: Gaussian
Link: Identity
Log likelihood = -885.44481
( 1) [perform]L = 1
Coefficient Std. err. z P>z [95% conf. interval]
perform
support .7139836 .024505 29.14 0.000 .6659548 .7620124
satis .5490609 .0335527 16.36 0.000 .4832987 .614823
branch
2 -.5815346 .1381258 -4.21 0.000 -.8522561 -.310813
3 .0468524 .138654 0.34 0.735 -.2249044 .3186092
4 -.462136 .1382752 -3.34 0.001 -.7331504 -.1911216
5 .3404709 .1383197 2.46 0.014 .0693693 .6115725
6 1.200632 .1401391 8.57 0.000 .9259649 1.4753
7 .1456119 .1394184 1.04 0.296 -.1276431 .4188669
8 .1823682 .1394647 1.31 0.191 -.0909775 .455714
9 .0231412 .138296 0.17 0.867 -.247914 .2941964
10 .9177335 .1441693 6.37 0.000 .635167 1.2003
11 .3861063 .1388028 2.78 0.005 .1140578 .6581548
12 -.0760954 .1381769 -0.55 0.582 -.3469172 .1947264
13 .0474839 .1389987 0.34 0.733 -.2249486 .3199163
14 .5582964 .1391763 4.01 0.000 .2855158 .831077
15 .8265082 .1501036 5.51 0.000 .5323105 1.120706
16 -.4437192 .1394772 -3.18 0.001 -.7170895 -.1703488
17 -.2131928 .138107 -1.54 0.123 -.4838776 .057492
18 .4292715 .1445243 2.97 0.003 .1460091 .7125339
19 .6424994 .1424461 4.51 0.000 .3633101 .9216888
20 .4594176 .1389425 3.31 0.001 .1870954 .7317398
21 .8956857 .1439646 6.22 0.000 .6135202 1.177851
22 .096672 .1380901 0.70 0.484 -.1739797 .3673236
23 .4863984 .1400319 3.47 0.001 .2119408 .7608559
24 .513326 .1396746 3.68 0.000 .2395688 .7870832
25 .1286559 .1397268 0.92 0.357 -.1452035 .4025154
26 .669922 .1418006 4.72 0.000 .391998 .947846
27 -.0151282 .1401642 -0.11 0.914 -.289845 .2595886
28 .16641 .1381439 1.20 0.228 -.1043471 .4371671
29 -.6088293 .1393606 -4.37 0.000 -.881971 -.3356876
30 1.15589 .1449833 7.97 0.000 .871728 1.440052
31 .5958819 .1381038 4.31 0.000 .3252034 .8665605
32 .1719484 .1380808 1.25 0.213 -.098685 .4425817
33 .395337 .1436668 2.75 0.006 .1137552 .6769188
34 -.6017857 .1382228 -4.35 0.000 -.8726973 -.330874
35 -.0230875 .1385286 -0.17 0.868 -.2945986 .2484237
36 .2623954 .1384524 1.90 0.058 -.0089664 .5337571
37 .5017414 .1418911 3.54 0.000 .22364 .7798427
38 1.210847 .1401491 8.64 0.000 .9361596 1.485534
39 .7535965 .1387326 5.43 0.000 .4816857 1.025507
40 .8522359 .1389066 6.14 0.000 .579984 1.124488
41 .5151008 .1384598 3.72 0.000 .2437247 .786477
42 .5951251 .1387706 4.29 0.000 .3231398 .8671105
43 .6375748 .1407626 4.53 0.000 .3616852 .9134643
44 .8046811 .1410768 5.70 0.000 .5281757 1.081187
45 .4991278 .1474609 3.38 0.001 .2101098 .7881458
46 .760281 .1411274 5.39 0.000 .4836763 1.036886
47 -.0705665 .1384529 -0.51 0.610 -.3419292 .2007963
48 .9216263 .1439826 6.40 0.000 .6394256 1.203827
49 .6474784 .1382762 4.68 0.000 .376462 .9184948
50 .261228 .1383697 1.89 0.059 -.0099716 .5324276
51 .4130079 .1415381 2.92 0.004 .1355984 .6904174
52 .198901 .1416375 1.40 0.160 -.0787034 .4765054
53 .1324934 .1386533 0.96 0.339 -.1392621 .4042489
54 .9498633 .1420625 6.69 0.000 .6714258 1.228301
55 .2367334 .1385218 1.71 0.087 -.0347644 .5082312
56 .165609 .1396473 1.19 0.236 -.1080947 .4393128
57 .1669833 .1387411 1.20 0.229 -.1049443 .4389108
58 .2675435 .1403303 1.91 0.057 -.0074989 .5425859
59 -.2295663 .1388381 -1.65 0.098 -.5016839 .0425513
60 -.7067141 .1383955 -5.11 0.000 -.9779643 -.435464
61 .9114248 .138265 6.59 0.000 .6404304 1.182419
62 .6805134 .1385357 4.91 0.000 .4089884 .9520384
63 -.0306791 .1381078 -0.22 0.824 -.3013655 .2400073
64 .0755469 .1381387 0.55 0.584 -.1951999 .3462938
65 .6785538 .1419577 4.78 0.000 .4003218 .9567859
66 .002009 .1381135 0.01 0.988 -.2686885 .2727065
67 .6825912 .1417638 4.81 0.000 .4047393 .9604431
68 .2698958 .1381926 1.95 0.051 -.0009566 .5407483
69 .4812352 .1390728 3.46 0.001 .2086576 .7538129
70 -.3764502 .1390206 -2.71 0.007 -.6489256 -.1039748
71 .7262577 .1403353 5.18 0.000 .4512055 1.00131
72 .7607011 .1435909 5.30 0.000 .4792681 1.042134
73 .1532976 .1381588 1.11 0.267 -.1174887 .424084
74 .7704471 .1383511 5.57 0.000 .4992839 1.04161
75 .0521144 .1381002 0.38 0.706 -.218557 .3227857
L 1 (constrained)
_cons 4.653742 .098802 47.10 0.000 4.460093 4.84739
var(L) 1.53e-34 6.66e-19 . .
var(e.perform) .1906537 .0069616 .177486 .2047983
.
end of do-file
. do "C:\Users\rseg6065\AppData\Local\Temp\STD77e4_0000 00.tmp"
. use https://www.stata-press.com/data/r18/gsem_multmed
(Fictional job-performance data)
. gsem (perform<-support satis M1[branch] L, regress)
Fitting fixed-effects model:
Iteration 0: log likelihood = -1318.6577
Iteration 1: log likelihood = -1318.6577
Refining starting values:
Grid node 0: log likelihood = -1778.9315
Fitting full model:
Iteration 0: log likelihood = -1778.9315 (not concave)
Iteration 1: log likelihood = -1423.7726 (not concave)
Iteration 2: log likelihood = -1394.8369 (not concave)
Iteration 3: log likelihood = -1391.9978 (not concave)
Iteration 4: log likelihood = -1390.8638 (not concave)
Iteration 5: log likelihood = -1390.4104 (not concave)
Iteration 6: log likelihood = -1390.3198 (not concave)
Iteration 7: log likelihood = -1390.2473 (not concave)
Iteration 8: log likelihood = -1390.24 (not concave)
Iteration 9: log likelihood = -1390.2393 (not concave)
Iteration 10: log likelihood = -1390.2387 (not concave)
Iteration 11: log likelihood = -1390.2387 (not concave)
Iteration 12: log likelihood = -1390.2386 (not concave)
Iteration 13: log likelihood = -1390.2386 (not concave)
Iteration 14: log likelihood = -1390.2386 (not concave)
Iteration 15: log likelihood = -1390.2386 (not concave)
Iteration 16: log likelihood = -1390.2386 (not concave)
Iteration 17: log likelihood = -1390.2386 (not concave)
Iteration 18: log likelihood = -1390.2386 (not concave)
Iteration 19: log likelihood = -1390.2386 (not concave)
Iteration 20: log likelihood = -1390.2386 (not concave)
Iteration 21: log likelihood = -1390.2386 (not concave)
Iteration 22: log likelihood = -1390.2386 (not concave)
Iteration 23: log likelihood = -1390.2386 (not concave)
Iteration 24: log likelihood = -1390.2386 (not concave)
Iteration 25: log likelihood = -1390.2386 (not concave)
Iteration 26: log likelihood = -1390.2386 (not concave)
Iteration 27: log likelihood = -1390.2386 (not concave)
Iteration 28: log likelihood = -1390.2386 (not concave)
Iteration 29: log likelihood = -1390.2386 (not concave)
Iteration 30: log likelihood = -1390.2386 (not concave)
Iteration 31: log likelihood = -1390.2386 (not concave)
Iteration 32: log likelihood = -1390.2386 (not concave)
Iteration 33: log likelihood = -1390.2386 (not concave)
Iteration 34: log likelihood = -1390.2386 (not concave)
Iteration 35: log likelihood = -1390.2381 (not concave)
Iteration 36: log likelihood = -1390.2381 (not concave)
Iteration 37: log likelihood = -1390.2345 (not concave)
Iteration 38: log likelihood = -1390.2342 (not concave)
Iteration 39: log likelihood = -1390.2319 (not concave)
Iteration 40: log likelihood = -1390.2282 (not concave)
Iteration 41: log likelihood = -1390.2268 (not concave)
Iteration 42: log likelihood = -1390.2266 (not concave)
Iteration 43: log likelihood = -1390.2248 (not concave)
Iteration 44: log likelihood = -1390.177 (not concave)
Iteration 45: log likelihood = -1389.8712 (not concave)
Iteration 46: log likelihood = -1389.749 (not concave)
Iteration 47: log likelihood = -1389.7245 (not concave)
Iteration 48: log likelihood = -1384.7023 (not concave)
Iteration 49: log likelihood = -1380.6902 (not concave)
Iteration 50: log likelihood = -1379.8898 (not concave)
Iteration 51: log likelihood = -1369.5935 (not concave)
Iteration 52: log likelihood = -1369.3379 (not concave)
Iteration 53: log likelihood = -1259.0283 (not concave)
Iteration 54: log likelihood = -1218.0217 (not concave)
Iteration 55: log likelihood = -1096.0902 (not concave)
Iteration 56: log likelihood = -1075.3566
Iteration 57: log likelihood = -1047.2643 (not concave)
Iteration 58: log likelihood = -1047.0937
Iteration 59: log likelihood = -1035.5694
Iteration 60: log likelihood = -1033.3888 (not concave)
Iteration 61: log likelihood = -1033.3888 (not concave)
Iteration 62: log likelihood = -1033.3887 (not concave)
Iteration 63: log likelihood = -1033.3887
Iteration 64: log likelihood = -1033.3878 (not concave)
Iteration 65: log likelihood = -1033.3868 (not concave)
Iteration 66: log likelihood = -1033.3868 (not concave)
Iteration 67: log likelihood = -1033.3868
Generalized structural equation model Number of obs = 1,500
Response: perform
Family: Gaussian
Link: Identity
Log likelihood = -1033.3868
( 1) [perform]M1[branch] = 1
( 2) [perform]L = 1
Coefficient Std. err. z P>z [95% conf. interval]
perform
support .6981603 .0250434 27.88 0.000 .6490762 .7472444
satis .6042986 .03364 17.96 0.000 .5383654 .6702317
M1[branch] 1 (constrained)
L 1 (constrained)
_cons 4.986597 .0489469 101.88 0.000 4.890663 5.082531
var(M1[branch]) .1695987 .0302887 .1195105 .2406796
var(L) 4.51e-35 4.08e-19 . .
var(e.perform) .2010552 .0075452 .1867976 .2164011
.
end of do-file
.
I’m running three different commands in SAS that should give me the same results, where the cluster ID is branch
Command 1 and Command 2 give me the same result
However, Command 3, which should give me the same result does not.
Can someone please explain why Command 2 does not give me the same results as Command 3?
For Command 1 and Command 2,
The coefficeints on support and satis are 0.7139836 and 0.5490609 respectively
However for Command 3, ...
The coefficeints on support and satis are 0.6981603 and 0.6042986 respectively
Is the reason possible because command 3 uses random effects and command 2 uses fixed effects?
support .7139836 .0251594 28.38 0.000 .6646302 .7633371
satis .5490609
Variables include:
branch [large department store in 75 locations | cluster variable or group variable]
perform (Y variable) job performance [from 1500 employees]
satis (M variable) job satisfaction [from 1500 employees]
support (X variable) perceived support from managers
Command 1: Using xtreg
use https://www.stata-press.com/data/r18/gsem_multmed
xtset branch
xtreg perform support satis, fe
Command 2: Using gsem
use https://www.stata-press.com/data/r18/gsem_multmed
gsem (perform<-support satis i.branch L, regress)
Command 3: Using gsem
use https://www.stata-press.com/data/r18/gsem_multmed
gsem (perform<-support satis M1[branch] L, regress)
Any help would be really appreciated here?
The results from all 3 commands are below.
. do "C:\Users\rseg6065\AppData\Local\Temp\STD77e4_0000 00.tmp"
. use https://www.stata-press.com/data/r18/gsem_multmed
(Fictional job-performance data)
. xtset branch
Panel variable: branch (balanced)
. xtreg perform support satis, fe
Fixed-effects (within) regression Number of obs = 1,500
Group variable: branch Number of groups = 75
R-squared: Obs per group:
Within = 0.5317 min = 20
Between = 0.6588 avg = 20.0
Overall = 0.5392 max = 20
F(2,1423) = 807.74
corr(u_i, Xb) = 0.2744 Prob > F = 0.0000
perform Coefficient Std. err. t P>t [95% conf. interval]
support .7139836 .0251594 28.38 0.000 .6646302 .7633371
satis .5490609 .0344488 15.94 0.000 .4814851 .6166367
_cons 4.987632 .0115951 430.15 0.000 4.964887 5.010377
sigma_u .4419321
sigma_e .44829979
rho .49284752 (fraction of variance due to u_i)
F test that all u_i=0: F(74, 1423) = 15.03 Prob > F = 0.0000
.
end of do-file
. do "C:\Users\rseg6065\AppData\Local\Temp\STD77e4_0000 00.tmp"
. use https://www.stata-press.com/data/r18/gsem_multmed
(Fictional job-performance data)
. gsem (perform<-support satis i.branch L, regress)
Fitting fixed-effects model:
Iteration 0: log likelihood = -885.44481
Iteration 1: log likelihood = -885.44481
Refining starting values:
Grid node 0: log likelihood = -1629.4487
Fitting full model:
Iteration 0: log likelihood = -1629.4487 (not concave)
Iteration 1: log likelihood = -1486.8896 (not concave)
Iteration 2: log likelihood = -1425.1065 (not concave)
Iteration 3: log likelihood = -1401.0718 (not concave)
Iteration 4: log likelihood = -1398.7055 (not concave)
Iteration 5: log likelihood = -1396.8134 (not concave)
Iteration 6: log likelihood = -1396.4355 (not concave)
Iteration 7: log likelihood = -1396.3599 (not concave)
Iteration 8: log likelihood = -1396.3523 (not concave)
Iteration 9: log likelihood = -1396.3463 (not concave)
Iteration 10: log likelihood = -1396.346 (not concave)
Iteration 11: log likelihood = -1396.3457 (not concave)
Iteration 12: log likelihood = -1396.3457 (not concave)
Iteration 13: log likelihood = -1396.3457 (not concave)
Iteration 14: log likelihood = -1396.3457 (not concave)
Iteration 15: log likelihood = -1396.3457 (not concave)
Iteration 16: log likelihood = -1396.3457 (not concave)
Iteration 17: log likelihood = -1396.3457 (not concave)
Iteration 18: log likelihood = -1396.3457 (not concave)
Iteration 19: log likelihood = -1396.3457 (not concave)
Iteration 20: log likelihood = -1396.3457 (not concave)
Iteration 21: log likelihood = -1396.3457 (not concave)
Iteration 22: log likelihood = -1396.3457 (not concave)
Iteration 23: log likelihood = -1396.3457 (not concave)
Iteration 24: log likelihood = -1396.3457 (not concave)
Iteration 25: log likelihood = -1396.3457 (not concave)
Iteration 26: log likelihood = -1396.3457 (not concave)
Iteration 27: log likelihood = -1396.3457 (not concave)
Iteration 28: log likelihood = -1396.3457 (not concave)
Iteration 29: log likelihood = -1396.3457 (not concave)
Iteration 30: log likelihood = -1396.3457 (not concave)
Iteration 31: log likelihood = -1396.3457 (not concave)
Iteration 32: log likelihood = -1396.3457 (not concave)
Iteration 33: log likelihood = -1396.3454 (not concave)
Iteration 34: log likelihood = -1396.3454 (not concave)
Iteration 35: log likelihood = -1396.3436 (not concave)
Iteration 36: log likelihood = -1396.3436 (not concave)
Iteration 37: log likelihood = -1396.3434 (not concave)
Iteration 38: log likelihood = -1396.3291 (not concave)
Iteration 39: log likelihood = -1396.3277 (not concave)
Iteration 40: log likelihood = -1396.2545 (not concave)
Iteration 41: log likelihood = -1396.1374 (not concave)
Iteration 42: log likelihood = -1395.9499 (not concave)
Iteration 43: log likelihood = -1395.9125 (not concave)
Iteration 44: log likelihood = -1394.9524 (not concave)
Iteration 45: log likelihood = -1394.5685 (not concave)
Iteration 46: log likelihood = -1393.3396 (not concave)
Iteration 47: log likelihood = -1393.2782 (not concave)
Iteration 48: log likelihood = -1391.7052 (not concave)
Iteration 49: log likelihood = -1391.0764 (not concave)
Iteration 50: log likelihood = -1382.9928 (not concave)
Iteration 51: log likelihood = -892.31152
Iteration 52: log likelihood = -886.52405 (not concave)
Iteration 53: log likelihood = -885.44561 (not concave)
Iteration 54: log likelihood = -885.44481 (not concave)
Iteration 55: log likelihood = -885.44481 (not concave)
Iteration 56: log likelihood = -885.44481 (not concave)
Iteration 57: log likelihood = -885.44481 (backed up)
Generalized structural equation model Number of obs = 1,500
Response: perform
Family: Gaussian
Link: Identity
Log likelihood = -885.44481
( 1) [perform]L = 1
Coefficient Std. err. z P>z [95% conf. interval]
perform
support .7139836 .024505 29.14 0.000 .6659548 .7620124
satis .5490609 .0335527 16.36 0.000 .4832987 .614823
branch
2 -.5815346 .1381258 -4.21 0.000 -.8522561 -.310813
3 .0468524 .138654 0.34 0.735 -.2249044 .3186092
4 -.462136 .1382752 -3.34 0.001 -.7331504 -.1911216
5 .3404709 .1383197 2.46 0.014 .0693693 .6115725
6 1.200632 .1401391 8.57 0.000 .9259649 1.4753
7 .1456119 .1394184 1.04 0.296 -.1276431 .4188669
8 .1823682 .1394647 1.31 0.191 -.0909775 .455714
9 .0231412 .138296 0.17 0.867 -.247914 .2941964
10 .9177335 .1441693 6.37 0.000 .635167 1.2003
11 .3861063 .1388028 2.78 0.005 .1140578 .6581548
12 -.0760954 .1381769 -0.55 0.582 -.3469172 .1947264
13 .0474839 .1389987 0.34 0.733 -.2249486 .3199163
14 .5582964 .1391763 4.01 0.000 .2855158 .831077
15 .8265082 .1501036 5.51 0.000 .5323105 1.120706
16 -.4437192 .1394772 -3.18 0.001 -.7170895 -.1703488
17 -.2131928 .138107 -1.54 0.123 -.4838776 .057492
18 .4292715 .1445243 2.97 0.003 .1460091 .7125339
19 .6424994 .1424461 4.51 0.000 .3633101 .9216888
20 .4594176 .1389425 3.31 0.001 .1870954 .7317398
21 .8956857 .1439646 6.22 0.000 .6135202 1.177851
22 .096672 .1380901 0.70 0.484 -.1739797 .3673236
23 .4863984 .1400319 3.47 0.001 .2119408 .7608559
24 .513326 .1396746 3.68 0.000 .2395688 .7870832
25 .1286559 .1397268 0.92 0.357 -.1452035 .4025154
26 .669922 .1418006 4.72 0.000 .391998 .947846
27 -.0151282 .1401642 -0.11 0.914 -.289845 .2595886
28 .16641 .1381439 1.20 0.228 -.1043471 .4371671
29 -.6088293 .1393606 -4.37 0.000 -.881971 -.3356876
30 1.15589 .1449833 7.97 0.000 .871728 1.440052
31 .5958819 .1381038 4.31 0.000 .3252034 .8665605
32 .1719484 .1380808 1.25 0.213 -.098685 .4425817
33 .395337 .1436668 2.75 0.006 .1137552 .6769188
34 -.6017857 .1382228 -4.35 0.000 -.8726973 -.330874
35 -.0230875 .1385286 -0.17 0.868 -.2945986 .2484237
36 .2623954 .1384524 1.90 0.058 -.0089664 .5337571
37 .5017414 .1418911 3.54 0.000 .22364 .7798427
38 1.210847 .1401491 8.64 0.000 .9361596 1.485534
39 .7535965 .1387326 5.43 0.000 .4816857 1.025507
40 .8522359 .1389066 6.14 0.000 .579984 1.124488
41 .5151008 .1384598 3.72 0.000 .2437247 .786477
42 .5951251 .1387706 4.29 0.000 .3231398 .8671105
43 .6375748 .1407626 4.53 0.000 .3616852 .9134643
44 .8046811 .1410768 5.70 0.000 .5281757 1.081187
45 .4991278 .1474609 3.38 0.001 .2101098 .7881458
46 .760281 .1411274 5.39 0.000 .4836763 1.036886
47 -.0705665 .1384529 -0.51 0.610 -.3419292 .2007963
48 .9216263 .1439826 6.40 0.000 .6394256 1.203827
49 .6474784 .1382762 4.68 0.000 .376462 .9184948
50 .261228 .1383697 1.89 0.059 -.0099716 .5324276
51 .4130079 .1415381 2.92 0.004 .1355984 .6904174
52 .198901 .1416375 1.40 0.160 -.0787034 .4765054
53 .1324934 .1386533 0.96 0.339 -.1392621 .4042489
54 .9498633 .1420625 6.69 0.000 .6714258 1.228301
55 .2367334 .1385218 1.71 0.087 -.0347644 .5082312
56 .165609 .1396473 1.19 0.236 -.1080947 .4393128
57 .1669833 .1387411 1.20 0.229 -.1049443 .4389108
58 .2675435 .1403303 1.91 0.057 -.0074989 .5425859
59 -.2295663 .1388381 -1.65 0.098 -.5016839 .0425513
60 -.7067141 .1383955 -5.11 0.000 -.9779643 -.435464
61 .9114248 .138265 6.59 0.000 .6404304 1.182419
62 .6805134 .1385357 4.91 0.000 .4089884 .9520384
63 -.0306791 .1381078 -0.22 0.824 -.3013655 .2400073
64 .0755469 .1381387 0.55 0.584 -.1951999 .3462938
65 .6785538 .1419577 4.78 0.000 .4003218 .9567859
66 .002009 .1381135 0.01 0.988 -.2686885 .2727065
67 .6825912 .1417638 4.81 0.000 .4047393 .9604431
68 .2698958 .1381926 1.95 0.051 -.0009566 .5407483
69 .4812352 .1390728 3.46 0.001 .2086576 .7538129
70 -.3764502 .1390206 -2.71 0.007 -.6489256 -.1039748
71 .7262577 .1403353 5.18 0.000 .4512055 1.00131
72 .7607011 .1435909 5.30 0.000 .4792681 1.042134
73 .1532976 .1381588 1.11 0.267 -.1174887 .424084
74 .7704471 .1383511 5.57 0.000 .4992839 1.04161
75 .0521144 .1381002 0.38 0.706 -.218557 .3227857
L 1 (constrained)
_cons 4.653742 .098802 47.10 0.000 4.460093 4.84739
var(L) 1.53e-34 6.66e-19 . .
var(e.perform) .1906537 .0069616 .177486 .2047983
.
end of do-file
. do "C:\Users\rseg6065\AppData\Local\Temp\STD77e4_0000 00.tmp"
. use https://www.stata-press.com/data/r18/gsem_multmed
(Fictional job-performance data)
. gsem (perform<-support satis M1[branch] L, regress)
Fitting fixed-effects model:
Iteration 0: log likelihood = -1318.6577
Iteration 1: log likelihood = -1318.6577
Refining starting values:
Grid node 0: log likelihood = -1778.9315
Fitting full model:
Iteration 0: log likelihood = -1778.9315 (not concave)
Iteration 1: log likelihood = -1423.7726 (not concave)
Iteration 2: log likelihood = -1394.8369 (not concave)
Iteration 3: log likelihood = -1391.9978 (not concave)
Iteration 4: log likelihood = -1390.8638 (not concave)
Iteration 5: log likelihood = -1390.4104 (not concave)
Iteration 6: log likelihood = -1390.3198 (not concave)
Iteration 7: log likelihood = -1390.2473 (not concave)
Iteration 8: log likelihood = -1390.24 (not concave)
Iteration 9: log likelihood = -1390.2393 (not concave)
Iteration 10: log likelihood = -1390.2387 (not concave)
Iteration 11: log likelihood = -1390.2387 (not concave)
Iteration 12: log likelihood = -1390.2386 (not concave)
Iteration 13: log likelihood = -1390.2386 (not concave)
Iteration 14: log likelihood = -1390.2386 (not concave)
Iteration 15: log likelihood = -1390.2386 (not concave)
Iteration 16: log likelihood = -1390.2386 (not concave)
Iteration 17: log likelihood = -1390.2386 (not concave)
Iteration 18: log likelihood = -1390.2386 (not concave)
Iteration 19: log likelihood = -1390.2386 (not concave)
Iteration 20: log likelihood = -1390.2386 (not concave)
Iteration 21: log likelihood = -1390.2386 (not concave)
Iteration 22: log likelihood = -1390.2386 (not concave)
Iteration 23: log likelihood = -1390.2386 (not concave)
Iteration 24: log likelihood = -1390.2386 (not concave)
Iteration 25: log likelihood = -1390.2386 (not concave)
Iteration 26: log likelihood = -1390.2386 (not concave)
Iteration 27: log likelihood = -1390.2386 (not concave)
Iteration 28: log likelihood = -1390.2386 (not concave)
Iteration 29: log likelihood = -1390.2386 (not concave)
Iteration 30: log likelihood = -1390.2386 (not concave)
Iteration 31: log likelihood = -1390.2386 (not concave)
Iteration 32: log likelihood = -1390.2386 (not concave)
Iteration 33: log likelihood = -1390.2386 (not concave)
Iteration 34: log likelihood = -1390.2386 (not concave)
Iteration 35: log likelihood = -1390.2381 (not concave)
Iteration 36: log likelihood = -1390.2381 (not concave)
Iteration 37: log likelihood = -1390.2345 (not concave)
Iteration 38: log likelihood = -1390.2342 (not concave)
Iteration 39: log likelihood = -1390.2319 (not concave)
Iteration 40: log likelihood = -1390.2282 (not concave)
Iteration 41: log likelihood = -1390.2268 (not concave)
Iteration 42: log likelihood = -1390.2266 (not concave)
Iteration 43: log likelihood = -1390.2248 (not concave)
Iteration 44: log likelihood = -1390.177 (not concave)
Iteration 45: log likelihood = -1389.8712 (not concave)
Iteration 46: log likelihood = -1389.749 (not concave)
Iteration 47: log likelihood = -1389.7245 (not concave)
Iteration 48: log likelihood = -1384.7023 (not concave)
Iteration 49: log likelihood = -1380.6902 (not concave)
Iteration 50: log likelihood = -1379.8898 (not concave)
Iteration 51: log likelihood = -1369.5935 (not concave)
Iteration 52: log likelihood = -1369.3379 (not concave)
Iteration 53: log likelihood = -1259.0283 (not concave)
Iteration 54: log likelihood = -1218.0217 (not concave)
Iteration 55: log likelihood = -1096.0902 (not concave)
Iteration 56: log likelihood = -1075.3566
Iteration 57: log likelihood = -1047.2643 (not concave)
Iteration 58: log likelihood = -1047.0937
Iteration 59: log likelihood = -1035.5694
Iteration 60: log likelihood = -1033.3888 (not concave)
Iteration 61: log likelihood = -1033.3888 (not concave)
Iteration 62: log likelihood = -1033.3887 (not concave)
Iteration 63: log likelihood = -1033.3887
Iteration 64: log likelihood = -1033.3878 (not concave)
Iteration 65: log likelihood = -1033.3868 (not concave)
Iteration 66: log likelihood = -1033.3868 (not concave)
Iteration 67: log likelihood = -1033.3868
Generalized structural equation model Number of obs = 1,500
Response: perform
Family: Gaussian
Link: Identity
Log likelihood = -1033.3868
( 1) [perform]M1[branch] = 1
( 2) [perform]L = 1
Coefficient Std. err. z P>z [95% conf. interval]
perform
support .6981603 .0250434 27.88 0.000 .6490762 .7472444
satis .6042986 .03364 17.96 0.000 .5383654 .6702317
M1[branch] 1 (constrained)
L 1 (constrained)
_cons 4.986597 .0489469 101.88 0.000 4.890663 5.082531
var(M1[branch]) .1695987 .0302887 .1195105 .2406796
var(L) 4.51e-35 4.08e-19 . .
var(e.perform) .2010552 .0075452 .1867976 .2164011
.
end of do-file
.
