Hi, I am trying to run a first-order four-factor model in Stata 15 SEM Builder:

Array
However, the run command in Builder is giving the wrong model. The model I want is:

sem (CONTROL -> c1 c2 c3) (AUTONOMY -> a2 a3) (PLEASURE -> p1 p2 p3) (SELFREAL -> s1 s2 s3), method(mlmv) stand

The Builder is running:

. sem (Control -> casp_a, ) (Control -> casp_b, ) (Control -> casp_c, ) (Autonomy -> casp_e, ) (Autonomy -> casp_f, ) (Ple
> asure -> casp_g, ) (Pleasure -> casp_h, ) (Pleasure -> casp_i, ) (SelfRealisation -> casp_j, ) (SelfRealisation -> casp_
> k, ) (SelfRealisation -> casp_l, ), covstruct(_lexogenous, diagonal) method(mlmv) latent(Control Autonomy Pleasure SelfR
> ealisation ) cov( Control*Autonomy Control*Pleasure Autonomy*Pleasure Pleasure*SelfRealisation SelfRealisation*Control S
> elfRealisation*Autonomy) nocapslatent

Endogenous variables

Measurement: casp_a casp_b casp_c casp_e casp_f casp_g casp_h casp_i casp_j casp_k casp_l

Exogenous variables

Latent: Control Autonomy Pleasure SelfRealisation

Fitting saturated model:

Iteration 0: log likelihood = -22297.422
Iteration 1: log likelihood = -22293.692
Iteration 2: log likelihood = -22293.681
Iteration 3: log likelihood = -22293.681

Fitting baseline model:

Iteration 0: log likelihood = -27766.898
Iteration 1: log likelihood = -27766.867
Iteration 2: log likelihood = -27766.867

Fitting target model:

Iteration 0: log likelihood = -22458.465
Iteration 1: log likelihood = -22451.984
Iteration 2: log likelihood = -22451.944
Iteration 3: log likelihood = -22451.944

Structural equation model Number of obs = 2,006
Estimation method = mlmv
Log likelihood = -22451.944

( 1) [casp_a]Control = 1
( 2) [casp_e]Autonomy = 1
( 3) [casp_g]Pleasure = 1
( 4) [casp_j]SelfRealisation = 1
----------------------------------------------------------------------------------------------
| OIM
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
Measurement |
casp_a |
Control | 1 (constrained)
_cons | 3.031998 .0221224 137.06 0.000 2.988639 3.075357
---------------------------+----------------------------------------------------------------
casp_b |
Control | 1.100806 .0400939 27.46 0.000 1.022223 1.179388
_cons | 3.11491 .021331 146.03 0.000 3.073102 3.156718
---------------------------+----------------------------------------------------------------
casp_c |
Control | .9207606 .0371158 24.81 0.000 .8480149 .9935063
_cons | 3.309243 .0195946 168.89 0.000 3.270838 3.347647
---------------------------+----------------------------------------------------------------
casp_e |
Autonomy | 1 (constrained)
_cons | 2.969794 .023337 127.26 0.000 2.924055 3.015534
---------------------------+----------------------------------------------------------------
casp_f |
Autonomy | 1.061839 .0656554 16.17 0.000 .9331564 1.190521
_cons | 2.771949 .0233119 118.91 0.000 2.726258 2.817639
---------------------------+----------------------------------------------------------------
casp_g |
Pleasure | 1 (constrained)
_cons | 3.576865 .0165825 215.70 0.000 3.544364 3.609366
---------------------------+----------------------------------------------------------------
casp_h |
Pleasure | 1.091352 .0259677 42.03 0.000 1.040456 1.142248
_cons | 3.582129 .0156859 228.37 0.000 3.551385 3.612873
---------------------------+----------------------------------------------------------------
casp_i |
Pleasure | 1.028339 .0270565 38.01 0.000 .9753096 1.081369
_cons | 3.523929 .0158848 221.84 0.000 3.492796 3.555063
---------------------------+----------------------------------------------------------------
casp_j |
SelfRealisation | 1 (constrained)
_cons | 3.325054 .0175376 189.60 0.000 3.290681 3.359427
---------------------------+----------------------------------------------------------------
casp_k |
SelfRealisation | 1.166645 .026259 44.43 0.000 1.115178 1.218111
_cons | 3.264996 .0189483 172.31 0.000 3.227858 3.302134
---------------------------+----------------------------------------------------------------
casp_l |
SelfRealisation | 1.095507 .025528 42.91 0.000 1.045474 1.145541
_cons | 3.326322 .0180276 184.51 0.000 3.290989 3.361656
-----------------------------+----------------------------------------------------------------
var(e.casp_a)| .5132518 .0214054 .472967 .5569679
var(e.casp_b)| .3437549 .0191249 .3082422 .383359
var(e.casp_c)| .3700106 .0165761 .3389075 .4039681
var(e.casp_e)| .6488441 .0327711 .5876907 .7163611
var(e.casp_f)| .5924833 .0343444 .5288526 .6637701
var(e.casp_g)| .2230283 .0084948 .206985 .2403151
var(e.casp_h)| .1022459 .0059328 .0912548 .114561
var(e.casp_i)| .158637 .0068829 .1457044 .1727176
var(e.casp_j)| .2125981 .0085097 .1965568 .2299485
var(e.casp_k)| .170207 .0082863 .154717 .187248
var(e.casp_l)| .166333 .0077026 .151901 .1821361
var(Control)| .4678242 .0298848 .4127695 .5302221
var(Autonomy)| .4402568 .0376587 .3723025 .5206143
var(Pleasure)| .3283212 .0166175 .2973149 .362561
var(SelfRealisation)| .403452 .0190094 .3678628 .4424842
-----------------------------+----------------------------------------------------------------
cov(Control,Autonomy)| .2952353 .0208958 14.13 0.000 .2542804 .3361903
cov(Control,Pleasure)| .0947185 .011158 8.49 0.000 .0728492 .1165878
cov(Control,SelfRealisation)| .1732049 .0134671 12.86 0.000 .1468099 .1995999
cov(Autonomy,Pleasure)| .0790369 .012138 6.51 0.000 .0552469 .1028269
cov(Autonomy,SelfRealisation)| .1486125 .0141406 10.51 0.000 .1208973 .1763276
cov(Pleasure,SelfRealisation)| .3023035 .0135177 22.36 0.000 .2758092 .3287978
----------------------------------------------------------------------------------------------
LR test of model vs. saturated: chi2(38) = 316.53, Prob > chi2 = 0.0000
.
Appreciate any advice. Thank you!