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st: Odd SEM Results


From   Joseph Trubisz <[email protected]>
To   [email protected]
Subject   st: Odd SEM Results
Date   Sat, 03 Aug 2013 12:38:54 -0400

Greetings...

I probably am just missing something, but I don't know what.
I'm attempting to use sembuilder to create the diagram from Acock's SEM book, specifically the example
as shown on p.188.

If I use sembuilder, it generates the following output:

. sem (Intercept@1 -> bmi01) (Intercept@1 -> bmi02) (Intercept@1 -> bmi03) (Intercept@1 -> bmi05) (Interc
> ept@1 -> bmi06) (Intercept@1 -> bmi07) (Intercept@1 -> bmi08) (Intercept@1 -> bmi09) (Slope@0 -> bmi01)
> (Slope@1 -> bmi02) (Slope@2 -> bmi03) (Slope@4 -> bmi05) (Slope@5 -> bmi06) (Slope@6 -> bmi07) (Slope@
> 7 -> bmi08) (Slope@8 -> bmi09) (_cons -> Intercept) (_cons -> Slope) (male -> Intercept) (male -> Slope
> ) (wgtc -> Intercept) (wgtc -> Slope) if bmi01!=.|bmi02!=.|bmi03!=.|bmi05!=.|bmi06!=.|bmi07!=.|bmi08!=.
> |bmi09!=., method(mlmv) latent(Intercept Slope ) var( e.Intercept*e.Slope) nocapslatent noconstant
note: Missing values found in observed exogenous variables. Using the noxconditional behavior. Specify
   the forcexconditional option to override this behavior.
Endogenous variables

Measurement:  bmi01 bmi02 bmi03 bmi05 bmi06 bmi07 bmi08 bmi09
Latent:       Intercept Slope

Exogenous variables

Observed:     male wgtc

Fitting saturated model:

Iteration 0:   log likelihood = -30162.223  
Iteration 1:   log likelihood = -29297.714  
Iteration 2:   log likelihood = -28707.587  
Iteration 3:   log likelihood = -28564.929  
Iteration 4:   log likelihood = -28557.353  
Iteration 5:   log likelihood = -28557.204  
Iteration 6:   log likelihood = -28557.204  

Fitting baseline model:

Iteration 0:   log likelihood = -36523.419  
Iteration 1:   log likelihood = -36520.845  
Iteration 2:   log likelihood = -36520.836  
Iteration 3:   log likelihood = -36520.836  

Fitting target model:

Iteration 0:   log likelihood =  -52919.48  (not concave)
Iteration 1:   log likelihood = -52675.161  (not concave)
Iteration 2:   log likelihood = -52171.219  (not concave)
Iteration 3:   log likelihood = -49397.835  (not concave)
Iteration 4:   log likelihood = -42220.623  (not concave)
Iteration 5:   log likelihood = -39274.796  
Iteration 6:   log likelihood =  -38652.54  
Iteration 7:   log likelihood = -34772.666  
Iteration 8:   log likelihood = -32169.128  
Iteration 9:   log likelihood = -31367.639  
Iteration 10:  log likelihood = -30934.922  
Iteration 11:  log likelihood = -30910.018  
Iteration 12:  log likelihood = -30909.236  
Iteration 13:  log likelihood = -30909.234  

Structural equation model                       Number of obs      =      1581
Estimation method  = mlmv
Log likelihood     = -30909.234

( 1)  [bmi01]Intercept = 1
( 2)  [bmi02]Intercept = 1
( 3)  [bmi02]Slope = 1
( 4)  [bmi03]Intercept = 1
( 5)  [bmi03]Slope = 2
( 6)  [bmi05]Intercept = 1
( 7)  [bmi05]Slope = 4
( 8)  [bmi06]Intercept = 1
( 9)  [bmi06]Slope = 5
(10)  [bmi07]Intercept = 1
(11)  [bmi07]Slope = 6
(12)  [bmi08]Intercept = 1
(13)  [bmi08]Slope = 7
(14)  [bmi09]Intercept = 1
(15)  [bmi09]Slope = 8
(16)  [bmi01]_cons = 0
(17)  [bmi02]_cons = 0
(18)  [bmi03]_cons = 0
(19)  [bmi05]_cons = 0
(20)  [bmi06]_cons = 0
(21)  [bmi07]_cons = 0
(22)  [bmi08]_cons = 0
(23)  [bmi09]_cons = 0
--------------------------------------------------------------------------------
            |                 OIM
            |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
Structural     |
Intercept <- |
       male |   26.90551   .6496371    41.42   0.000     25.63225    28.17878
       wgtc |   6.996785   .6003745    11.65   0.000     5.820072    8.173497
-------------+----------------------------------------------------------------
Slope <-     |
       male |   .3657208     .02104    17.38   0.000     .3244831    .4069584
       wgtc |   .0889063   .0194718     4.57   0.000     .0507423    .1270703
---------------+----------------------------------------------------------------
Measurement    |
bmi01 <-     |
  Intercept |          1  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi02 <-     |
  Intercept |          1  (constrained)
      Slope |          1  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi03 <-     |
  Intercept |          1  (constrained)
      Slope |          2  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi05 <-     |
  Intercept |          1  (constrained)
      Slope |          4  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi06 <-     |
  Intercept |          1  (constrained)
      Slope |          5  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi07 <-     |
  Intercept |          1  (constrained)
      Slope |          6  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi08 <-     |
  Intercept |          1  (constrained)
      Slope |          7  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi09 <-     |
  Intercept |          1  (constrained)
      Slope |          8  (constrained)
      _cons |          0  (constrained)
---------------+----------------------------------------------------------------
Mean           |
       male |   .4990512   .0125749    39.69   0.000      .474405    .5236975
       wgtc |  -.0001655   .0192488    -0.01   0.993    -.0378925    .0375614
---------------+----------------------------------------------------------------
Variance       |
    e.bmi01 |   2.618815   .2046736                      2.246876    3.052323
    e.bmi02 |   4.086149   .2175673                      3.681222    4.535619
    e.bmi03 |   4.674361   .2320231                      4.241024    5.151974
    e.bmi05 |   5.778033   .2604252                      5.289505    6.311681
    e.bmi06 |   8.181968   .3511234                      7.521926    8.899928
    e.bmi07 |   3.794672   .1906747                      3.438769    4.187409
    e.bmi08 |    2.92201   .1689406                      2.608965    3.272618
    e.bmi09 |   3.308288   .2088301                      2.923295    3.743984
e.Intercept |   324.2532   11.61219                      302.2741    347.8304
    e.Slope |   .2448578   .0117764                      .2228311     .269062
       male |   .2499991   .0088918                      .2331651    .2680484
       wgtc |   .5851282   .0208269                      .5456996    .6274057
---------------+----------------------------------------------------------------
Covariance     |
e.Intercept  |
    e.Slope |   4.109434    .280162    14.67   0.000     3.560327    4.658542
-------------+----------------------------------------------------------------
male         |
       wgtc |  -.0751429   .0098082    -7.66   0.000    -.0943666   -.0559193
--------------------------------------------------------------------------------
LR test of model vs. saturated: chi2(45)  =   4704.06, Prob > chi2 = 0.0000


However, the output is nothing like what's in the book. However, if I type in 
exactly what's in the book (p.188), I get the correct results as shown below:  

. sem (Intercept@1 Slope@0->bmi01) (Intercept@1 Slope@1->bmi02) (Intercept@1 Slope@2->bmi03) (Intercept@1
> Slope@4->bmi05)(Intercept@1 Slope@5->bmi06)(Intercept@1 Slope@6->bmi07)(Intercept@1 Slope@7->bmi08)(In
> tercept@1 Slope@8->bmi09) (Intercept Slope<-male wgtc _cons) if bmi01!=.|bmi02!=.|bmi03!=.|bmi05!=.|bmi
> 06!=.|bmi07!=.|bmi08!=.|bmi09!=.,var(e.Intercept*e.Slope) method(mlmv) noconstant
note: Missing values found in observed exogenous variables. Using the noxconditional behavior. Specify
   the forcexconditional option to override this behavior.
Endogenous variables

Measurement:  bmi01 bmi02 bmi03 bmi05 bmi06 bmi07 bmi08 bmi09
Latent:       Intercept Slope

Exogenous variables

Observed:     male wgtc

Fitting saturated model:

Iteration 0:   log likelihood = -30162.223  
Iteration 1:   log likelihood = -29297.714  
Iteration 2:   log likelihood = -28707.587  
Iteration 3:   log likelihood = -28564.929  
Iteration 4:   log likelihood = -28557.353  
Iteration 5:   log likelihood = -28557.204  
Iteration 6:   log likelihood = -28557.204  

Fitting baseline model:

Iteration 0:   log likelihood = -36523.419  
Iteration 1:   log likelihood = -36520.845  
Iteration 2:   log likelihood = -36520.836  
Iteration 3:   log likelihood = -36520.836  

Fitting target model:

Iteration 0:   log likelihood =  -52919.48  (not concave)
Iteration 1:   log likelihood = -52663.873  (not concave)
Iteration 2:   log likelihood = -52499.164  (not concave)
Iteration 3:   log likelihood = -52371.927  (not concave)
Iteration 4:   log likelihood = -46362.021  (not concave)
Iteration 5:   log likelihood = -34630.285  (not concave)
Iteration 6:   log likelihood = -34303.836  (not concave)
Iteration 7:   log likelihood = -29724.362  
Iteration 8:   log likelihood =   -29095.8  
Iteration 9:   log likelihood = -28787.969  
Iteration 10:  log likelihood = -28750.647  
Iteration 11:  log likelihood =  -28750.02  
Iteration 12:  log likelihood = -28750.019  

Structural equation model                       Number of obs      =      1581
Estimation method  = mlmv
Log likelihood     = -28750.019

( 1)  [bmi01]Intercept = 1
( 2)  [bmi02]Intercept = 1
( 3)  [bmi02]Slope = 1
( 4)  [bmi03]Intercept = 1
( 5)  [bmi03]Slope = 2
( 6)  [bmi05]Intercept = 1
( 7)  [bmi05]Slope = 4
( 8)  [bmi06]Intercept = 1
( 9)  [bmi06]Slope = 5
(10)  [bmi07]Intercept = 1
(11)  [bmi07]Slope = 6
(12)  [bmi08]Intercept = 1
(13)  [bmi08]Slope = 7
(14)  [bmi09]Intercept = 1
(15)  [bmi09]Slope = 8
(16)  [bmi01]_cons = 0
(17)  [bmi02]_cons = 0
(18)  [bmi03]_cons = 0
(19)  [bmi05]_cons = 0
(20)  [bmi06]_cons = 0
(21)  [bmi07]_cons = 0
(22)  [bmi08]_cons = 0
(23)  [bmi09]_cons = 0
--------------------------------------------------------------------------------
            |                 OIM
            |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
Structural     |
Intercept <- |
       male |   1.555545   .2436739     6.38   0.000     1.077953    2.033137
       wgtc |   3.759441    .160021    23.49   0.000     3.445806    4.073077
      _cons |   24.85781    .170538   145.76   0.000     24.52356    25.19206
-------------+----------------------------------------------------------------
Slope <-     |
       male |   .0173321   .0271012     0.64   0.522    -.0357853    .0704495
       wgtc |   .0459197   .0178505     2.57   0.010     .0109333    .0809062
      _cons |   .3430045   .0189564    18.09   0.000     .3058506    .3801584
---------------+----------------------------------------------------------------
Measurement    |
bmi01 <-     |
  Intercept |          1  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi02 <-     |
  Intercept |          1  (constrained)
      Slope |          1  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi03 <-     |
  Intercept |          1  (constrained)
      Slope |          2  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi05 <-     |
  Intercept |          1  (constrained)
      Slope |          4  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi06 <-     |
  Intercept |          1  (constrained)
      Slope |          5  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi07 <-     |
  Intercept |          1  (constrained)
      Slope |          6  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi08 <-     |
  Intercept |          1  (constrained)
      Slope |          7  (constrained)
      _cons |          0  (constrained)
-------------+----------------------------------------------------------------
bmi09 <-     |
  Intercept |          1  (constrained)
      Slope |          8  (constrained)
      _cons |          0  (constrained)
---------------+----------------------------------------------------------------
Mean           |
       male |   .4990512   .0125749    39.69   0.000      .474405    .5236975
       wgtc |  -.0009276   .0192434    -0.05   0.962    -.0386439    .0367888
---------------+----------------------------------------------------------------
Variance       |
    e.bmi01 |   2.443884    .191981                      2.095144    2.850673
    e.bmi02 |     4.1472   .2157233                      3.745229    4.592315
    e.bmi03 |   4.772852   .2325326                       4.33818    5.251077
    e.bmi05 |   5.789807   .2596509                      5.302625    6.321749
    e.bmi06 |   8.228898   .3520222                       7.56708    8.948599
    e.bmi07 |   3.810727   .1909167                      3.454322    4.203904
    e.bmi08 |   2.922193   .1687984                      2.609396    3.272487
    e.bmi09 |   3.298484   .2089123                      2.913418    3.734444
e.Intercept |    20.5145   .8043478                      18.99706    22.15315
    e.Slope |    .189059   .0097265                       .170925    .2091168
       male |   .2499991   .0088918                      .2331651    .2680484
       wgtc |   .5849257   .0208131                      .5455228    .6271748
---------------+----------------------------------------------------------------
Covariance     |
e.Intercept  |
    e.Slope |  -.0272943   .0635517    -0.43   0.668    -.1518533    .0972647
-------------+----------------------------------------------------------------
male         |
       wgtc |  -.0747626   .0098037    -7.63   0.000    -.0939775   -.0555478
--------------------------------------------------------------------------------
LR test of model vs. saturated: chi2(43)  =    385.63, Prob > chi2 = 0.0000

Problem: I look at the command not working and comparing it to the command that does
work and I don't see the difference.

Can anyone point out to me where I might be going wrong?

TIA,
Joe     
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