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The relevant parts of the output have been bolded, and for many of the examples, some of the output has been omitted to save space.
LEM uses three-letter abbreviations for its statements. Those used in the following examples are explained below.
lat - latent: The number of latent variables
man - manifest: The number of manifest variables
dim - dimensions: The number of dimensions of each of the variables.
The number of dimensions for the latent variable(s) is given first.
lab - label: The names of the variables
mod - model: This specifies the model
dat - data: The data may be specified as the number of cases
occurring in each cell, or as a path to a text file. When including
frequencies, as shown in the examples below, it is assumed that the last
variable listed changes first (see page 8 of the LEM manual)
see - seed: Sets the seed
sta - start: The starting values (must equal 1 for each variable).
des - design: Specifies which parameters are equal to given values
or other parameters. 0 = the parameter is free to be estimated; positive
number = equal to other parameters with the same number; -1 = fixed.
The rows are the variables and the columns are the classes (e.g., column 1 =
class1-yes, column 2 = class1-no, column 3 = class2-yes, etc.) (see page 34 of the LEM manual)
rec - record - Specifies that the data are individual records (see page
83 of the LEM manual)
rco - record count - Specifies that the records are counts (frequencies)
(see page 83 of the LEM manual)
Page 33 Table 3.2
Complete independence model:
NOTE: There is a typographical error in the text, indicating that there
are 35 degrees of freedom for this model instead of 29.
lat 1
man 4
dim 1 3 2 2 3
lab X P A U C
mod X P|X A|X U|X C|X
dat [419 23 26 270 43 85
71 6 1 42 9 13
35 4 3 25 9 23
25 2 2 16 3 12
2 1 0 4 2 6
5 0 0 5 2 8]
*** STATISTICS *** Number of iterations = 2 Converge criterion = 0.0000000000 Seed random values = 855 X-squared = 368.6657 (0.0000) L-squared = 257.2604 (0.0000) Cressie-Read = 305.4123 (0.0000) Dissimilarity index = 0.1631 Degrees of freedom = 29 Log-likelihood = -2872.22958 Number of parameters = 6 (+1) Sample size = 1202.0 BIC(L-squared) = 51.5998 AIC(L-squared) = 199.2604 BIC(log-likelihood) = 5787.0096 AIC(log-likelihood) = 5756.4592
Two-class model:
lat 1
man 4
dim 2 3 2 2 3
lab X P A U C
mod X P|X A|X U|X C|X
dat [419 23 26 270 43 85
71 6 1 42 9 13
35 4 3 25 9 23
25 2 2 16 3 12
2 1 0 4 2 6
5 0 0 5 2 8]
Number of iterations = 286 Converge criterion = 0.0000009875 Seed random values = 2266 X-squared = 93.2545 (0.0000) L-squared = 79.3373 (0.0000) Cressie-Read = 86.9142 (0.0000) Dissimilarity index = 0.0721 Degrees of freedom = 22 Log-likelihood = -2783.26803 Number of parameters = 13 (+1) Sample size = 1202.0 BIC(L-squared) = -76.6811 AIC(L-squared) = 35.3373 BIC(log-likelihood) = 5658.7287 AIC(log-likelihood) = 5592.5361
Three-class model:
NOTE: It is explained on page 32 in the book why the degrees of freedom is
16. This is because that the probability prob(P = 3| X=2) is virtually set to be
zero.
lat 1
man 4
dim 3 3 2 2 3
lab X P A U C
mod X P|X eq2 A|X U|X C|X
dat [419 23 26 270 43 85
71 6 1 42 9 13
35 4 3 25 9 23
25 2 2 16 3 12
2 1 0 4 2 6
5 0 0 5 2 8]
des [ 0 0 0 0 0 -1 0 0 0]
sta P|X [.8 .1 .1 .9 .1 0 .8 .1 .1]
seed 12137
*** STATISTICS ***
Number of iterations = 640
Converge criterion = 0.0000009717
Seed random values = 12137
X-squared = 23.5283 (0.1003)
L-squared = 21.8921 (0.1467)
Cressie-Read = 22.6134 (0.1245)
Dissimilarity index = 0.0273
Degrees of freedom = 16
Log-likelihood = -2754.54543
Number of parameters = 19 (+1)
Sample size = 1202.0
BIC(L-squared) = -91.5758
AIC(L-squared) = -10.1079
BIC(log-likelihood) = 5643.8340
AIC(log-likelihood) = 5547.0909
WARNING: no information is provided on identification of parameters
*** FREQUENCIES ***
P A U C observed estimated std. res.
1 1 1 1 419.000 415.276 0.183
1 1 1 2 23.000 26.130 -0.612
1 1 1 3 26.000 27.881 -0.356
1 1 2 1 270.000 272.929 -0.177
1 1 2 2 43.000 37.588 0.883
1 1 2 3 85.000 77.571 0.844
1 2 1 1 71.000 69.751 0.150
1 2 1 2 6.000 5.694 0.128
1 2 1 3 1.000 1.925 -0.667
1 2 2 1 42.000 42.374 -0.057
1 2 2 2 9.000 10.102 -0.347
1 2 2 3 13.000 20.780 -1.707
2 1 1 1 35.000 35.021 -0.004
2 1 1 2 4.000 2.588 0.878
2 1 1 3 3.000 2.542 0.287
2 1 2 1 25.000 26.503 -0.292
2 1 2 2 9.000 10.067 -0.336
2 1 2 3 23.000 25.563 -0.507
2 2 1 1 25.000 25.823 -0.162
2 2 1 2 2.000 2.114 -0.079
2 2 1 3 2.000 0.732 1.482
2 2 2 1 16.000 15.818 0.046
2 2 2 2 3.000 3.948 -0.477
2 2 2 3 12.000 8.281 1.292
3 1 1 1 2.000 2.593 -0.368
3 1 1 2 1.000 0.312 1.231
3 1 1 3 0.000 0.368 -0.607
3 1 2 1 4.000 3.597 0.213
3 1 2 2 2.000 3.603 -0.844
3 1 2 3 6.000 9.869 -1.231
3 2 1 1 5.000 5.570 -0.242
3 2 1 2 0.000 0.473 -0.687
3 2 1 3 0.000 0.207 -0.455
3 2 2 1 5.000 3.745 0.649
3 2 2 2 2.000 1.382 0.525
3 2 2 3 8.000 3.282 2.604
*** PSEUDO R-SQUARED MEASURES ***
* P(P|X) *
baseline fitted R-squared
entropy 0.5182 0.4433 0.1445
qualitative variance 0.1392 0.1247 0.1041
classification error 0.1614 0.1614 0.0000
-2/N*log-likelihood 1.0363 0.8866 0.1445/0.1303
likelihood^(-2/N) 2.8188 2.4268 0.1391/0.2156
* P(A|X) *
baseline fitted R-squared
entropy 0.4784 0.2248 0.5302
qualitative variance 0.1506 0.0765 0.4922
classification error 0.1847 0.1072 0.4198
-2/N*log-likelihood 0.9569 0.4495 0.5302/0.3366
likelihood^(-2/N) 2.6035 1.5676 0.3979/0.6461
* P(U|X) *
baseline fitted R-squared
entropy 0.6923 0.5727 0.1729
qualitative variance 0.2496 0.1997 0.1998
classification error 0.4800 0.3185 0.3365
-2/N*log-likelihood 1.3847 1.1453 0.1729/0.1932
likelihood^(-2/N) 3.9936 3.1434 0.2129/0.2840
* P(C|X) *
baseline fitted R-squared
entropy 0.7006 0.4918 0.2981
qualitative variance 0.1929 0.1261 0.3464
classification error 0.2354 0.1510 0.3585
-2/N*log-likelihood 1.4012 0.9835 0.2981/0.2946
likelihood^(-2/N) 4.0600 2.6738 0.3414/0.4530
*** LOG-LINEAR PARAMETERS ***
* TABLE X [or P(X)] *
effect beta exp(beta)
X
1 -0.4872 0.6143
2 0.7935 2.2112
3 -0.3063 0.7361
* TABLE XA [or P(A|X)] *
effect beta exp(beta)
A
1 3.5040 33.2476
2 -3.5040 0.0301
XA
1 1 -2.9463 0.0525
1 2 2.9463 19.0359
2 1 6.8447 938.8669
2 2 -6.8447 0.0011
3 1 -3.8983 0.0203
3 2 3.8983 49.3208
* TABLE XU [or P(U|X)] *
effect beta exp(beta)
U
1 -0.3916 0.6760
2 0.3916 1.4793
XU
1 1 -1.3181 0.2676
1 2 1.3181 3.7362
2 1 0.6216 1.8620
2 2 -0.6216 0.5371
3 1 0.6964 2.0066
3 2 -0.6964 0.4984
* TABLE XC [or P(C|X)] *
effect beta exp(beta)
C
1 1.1275 3.0880
2 -0.5092 0.6010
3 -0.6183 0.5389
XC
1 1 -1.7732 0.1698
1 2 0.3144 1.3694
1 3 1.4589 4.3010
2 1 0.7170 2.0483
2 2 -0.4621 0.6300
2 3 -0.2550 0.7750
3 1 1.0562 2.8755
3 2 0.1477 1.1591
3 3 -1.2039 0.3000
*** (CONDITIONAL) PROBABILITIES ***
* P(X) *
1 0.1725
2 0.6208
3 0.2067
* P(P|X) *
1 | 1 0.6410
2 | 1 0.2561
3 | 1 0.1030
1 | 2 0.9431
2 | 2 0.0569
3 | 2 0.0000 *
1 | 3 0.6897
2 | 3 0.2553
3 | 3 0.0550
* P(A|X) *
1 | 1 0.7531
2 | 1 0.2469
1 | 2 1.0000
2 | 2 0.0000
1 | 3 0.3124
2 | 3 0.6876
* P(U|X) *
1 | 1 0.0317
2 | 1 0.9683
1 | 2 0.6130
2 | 2 0.3870
1 | 3 0.6479
2 | 3 0.3521
* P(C|X) *
1 | 1 0.1431
2 | 1 0.2245
3 | 1 0.6324
1 | 2 0.8882
2 | 2 0.0532
3 | 2 0.0586
1 | 3 0.9119
2 | 3 0.0715
3 | 3 0.0166
*** LATENT CLASS OUTPUT ***
X 1 X 2 X 3
0.1725 0.6208 0.2067
P 1 0.6410 0.9431 0.6897
P 2 0.2561 0.0569 0.2553
P 3 0.1030 0.0000 0.0550
A 1 0.7531 1.0000 0.3124
A 2 0.2469 0.0000 0.6876
U 1 0.0317 0.6130 0.6479
U 2 0.9683 0.3870 0.3521
C 1 0.1431 0.8882 0.9119
C 2 0.2245 0.0532 0.0715
C 3 0.6324 0.0586 0.0166
E = 0.1208, lambda = 0.6814
page 40 Table 3.4
Unrestricted three-class model:
Well, it is almost unrestricted. There is virtually a constraint: prob(P=3|X=2) = 0). This is the model above. The input and output will be omitted here.
Specific value restrictions:
lat 1
man 4
dim 3 3 2 2 3
lab X C U A P
mod X
P|X eq2
A|X eq2
U|X eq2
C|X eq2
dat [419 23 26 270 43 85
71 6 1 42 9 13
35 4 3 25 9 23
25 2 2 16 3 12
2 1 0 4 2 6
5 0 0 5 2 8]
des [ 0 0 0 0 0 0 0 0 0 *P
0 0 -1 0 0 0 *A
0 0 0 0 -1 0 *U
0 0 0 0 0 0 0 0 -1] *C
sta P|X [.8 .1 .1 .8 .1 .1 .8 .1 .1]
sta A|X [.7 .3 0 1 .7 .3 ]
sta U|X [.7 .3 .7 .3 1 0 ]
sta C|X [.2 .4 .4 .2 .2 .6 .4 .6 0 ]
see 3497
ite 5000
Number of iterations = 277
Converge criterion = 0.0000009659
Seed random values = 3497
X-squared = 24.4548 (0.1407)
L-squared = 22.1326 (0.2261)
Cressie-Read = 23.3047 (0.1792)
Dissimilarity index = 0.0283
Degrees of freedom = 18
Log-likelihood = -2754.66571
Number of parameters = 17 (+1)
Sample size = 1202.0
BIC(L-squared) = -105.5187
AIC(L-squared) = -13.8674
BIC(log-likelihood) = 5629.8910
AIC(log-likelihood) = 5543.3314
WARNING: no information is provided on identification of parameters
Specific value and equality restrictions
lat 1
man 4
dim 3 3 2 2 3
lab X C U A P
mod X
P|X eq2
A|X eq2
U|X eq2
C|X eq2
dat [419 23 26 270 43 85
71 6 1 42 9 13
35 4 3 25 9 23
25 2 2 16 3 12
2 1 0 4 2 6
5 0 0 5 2 8]
des [ 1 2 0 0 0 0 1 2 0 *P
3 0 -1 0 3 0 *A
0 0 0 0 -1 0 *U
0 0 0 0 0 0 0 0 -1] *C
sta P|X [.8 .1 .1 .8 .1 .1 .8 .1 .1]
sta A|X [.7 .3 0 1 .7 .3 ]
sta U|X [.7 .3 .7 .3 1 0 ]
sta C|X [.2 .4 .4 .2 .2 .6 .4 .6 0 ]
see 3497
ite 5000
Number of iterations = 295
Converge criterion = 0.0000009806
Seed random values = 3497
X-squared = 27.0159 (0.1703)
L-squared = 25.5894 (0.2225)
Cressie-Read = 26.0216 (0.2056)
Dissimilarity index = 0.0285
Degrees of freedom = 21
Log-likelihood = -2756.39407
Number of parameters = 14 (+1)
Sample size = 1202.0
BIC(L-squared) = -123.3372
AIC(L-squared) = -16.4106
BIC(log-likelihood) = 5612.0725
AIC(log-likelihood) = 5540.7881
WARNING: no information is provided on identification of parameters
Page 43 Table 3.5
NOTE: The output in this table is from the code from the example immediately above.
*** (CONDITIONAL) PROBABILITIES *** * P(X) * 1 0.2229 2 0.1577 3 0.6194 * P(P|X) * 1 | 1 0.8872 2 | 1 0.0600 3 | 1 0.0529 1 | 2 0.1098 2 | 2 0.2284 3 | 2 0.6618 1 | 3 0.8872 2 | 3 0.0600 3 | 3 0.0529 * P(A|X) * 1 | 1 0.6173 2 | 1 0.3827 1 | 2 0.0000 * 2 | 2 1.0000 * 1 | 3 0.6173 2 | 3 0.3827 * P(U|X) * 1 | 1 0.3376 2 | 1 0.6624 1 | 2 0.7651 2 | 2 0.2349 1 | 3 1.0000 * 2 | 3 0.0000 * * P(C|X) * 1 | 1 0.6826 2 | 1 0.2597 3 | 1 0.0577 1 | 2 0.6487 2 | 2 0.2481 3 | 2 0.1031 1 | 3 0.9431 2 | 3 0.0569 3 | 3 0.0000 *
Page 47 Tables 4.1 and 4.2
lat 1
man 4
dim 1 2 2 2 2
lab X W A I V
mod X
W|X
A|X
I|X
V|X
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
*** STATISTICS ***
Number of iterations = 2
Converge criterion = 0.0000000000
Seed random values = 761
X-squared = 798.9635 (0.0000)
L-squared = 262.2663 (0.0000)
Cressie-Read = 477.9074 (0.0000)
Dissimilarity index = 0.1013
Degrees of freedom = 11
Log-likelihood = -2346.67463
Number of parameters = 4 (+1)
Sample size = 1402.0
BIC(L-squared) = 182.5641
AIC(L-squared) = 240.2663
BIC(log-likelihood) = 4722.3319
AIC(log-likelihood) = 4701.3493
Eigenvalues information matrix
1295.8331 1141.6413 392.0427 192.9211
NOTE: Table 4.1
*** FREQUENCIES *** W A I V observed estimated std. res. 1 1 1 1 27.000 0.980 26.285 1 1 1 2 0.000 0.390 -0.624 1 1 2 1 2.000 1.725 0.210 1 1 2 2 0.000 0.686 -0.828 1 2 1 1 16.000 11.981 1.161 1 2 1 2 0.000 4.766 -2.183 1 2 2 1 4.000 21.085 -3.721 1 2 2 2 1.000 8.388 -2.551 2 1 1 1 40.000 26.497 2.623 2 1 1 2 3.000 10.541 -2.323 2 1 2 1 32.000 46.631 -2.143 2 1 2 2 2.000 18.550 -3.843 2 2 1 1 339.000 323.968 0.835 2 2 1 2 83.000 128.877 -4.041 2 2 2 1 543.000 570.133 -1.136 2 2 2 2 310.000 226.803 5.524
NOTE: Table 4.2
*** (CONDITIONAL) PROBABILITIES *** * P(X) * 1 1.0000 (0.0000) * * P(W|X) * 1 | 1 0.0357 (0.0050) 2 | 1 0.9643 (0.0050) * P(A|X) * 1 | 1 0.0756 (0.0071) 2 | 1 0.9244 (0.0071) * P(I|X) * 1 | 1 0.3623 (0.0128) 2 | 1 0.6377 (0.0128) * P(V|X) * 1 | 1 0.7154 (0.0121) 2 | 1 0.2846 (0.0121)
Page 51 Table 4.4
Proctor's Model:
lat 1
man 4
dim 5 2 2 2 2
lab X W A I V
mod X
W|X eq2
A|X eq2
I|X eq2
V|X eq2
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
des [ 1 0 0 1 0 1 0 1 0 1
1 0 1 0 0 1 0 1 0 1
1 0 1 0 1 0 0 1 0 1
1 0 1 0 1 0 1 0 0 1]
*** STATISTICS ***
Number of iterations = 36
Converge criterion = 0.0000000491
Seed random values = 5911
X-squared = 137.4628 (0.0000)
L-squared = 138.1945 (0.0000)
Cressie-Read = 133.2954 (0.0000)
Dissimilarity index = 0.0575
Degrees of freedom = 10
Log-likelihood = -2284.63873
Number of parameters = 5 (+1)
Sample size = 1402.0
BIC(L-squared) = 65.7379
AIC(L-squared) = 118.1945
BIC(log-likelihood) = 4605.5057
AIC(log-likelihood) = 4579.2775
WARNING: no information is provided on identification of parameters
Item-specific error rates:
lat 1
man 4
dim 5 2 2 2 2
lab X W A I V
mod X
W|X eq2
A|X eq2
I|X eq2
V|X eq2
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
des [ 1 0 0 1 0 1 0 1 0 1
2 0 2 0 0 2 0 2 0 2
3 0 3 0 3 0 0 3 0 3
4 0 4 0 4 0 4 0 0 4]
*** STATISTICS ***
Number of iterations = 648
Converge criterion = 0.0000009938
Seed random values = 2794
X-squared = 36.6724 (0.0000)
L-squared = 36.4989 (0.0000)
Cressie-Read = 35.7604 (0.0000)
Dissimilarity index = 0.0234
Degrees of freedom = 7
Log-likelihood = -2233.79095
Number of parameters = 8 (+1)
Sample size = 1402.0
BIC(L-squared) = -14.2206
AIC(L-squared) = 22.4989
BIC(log-likelihood) = 4525.5471
AIC(log-likelihood) = 4483.5819
WARNING: no information is provided on identification of parameters
*** (CONDITIONAL) PROBABILITIES *** * P(X) * 1 0.0216 2 0.0330 3 0.2030 4 0.4578 5 0.2846
True-type-specific error rates:
lat 1
man 4
dim 5 2 2 2 2
lab X W A I V
mod X
W|X eq2
A|X eq2
I|X eq2
V|X eq2
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
des [ -1 0 0 2 0 3 0 4 0 5
-1 0 2 0 0 3 0 4 0 5
-1 0 2 0 3 0 0 4 0 5
-1 0 2 0 3 0 4 0 0 5]
sta W|X [1 0 .3 .7 .3 .7 .3 .7 .3 .7]
sta A|X [1 0 .3 .7 .3 .7 .3 .7 .3 .7]
sta I|X [1 0 .3 .7 .3 .7 .3 .7 .3 .7]
sta V|X [1 0 .3 .7 .3 .7 .3 .7 .3 .7]
see 12345
*** STATISTICS ***
Number of iterations = 181
Converge criterion = 0.0000009650
Seed random values = 12345
X-squared = 86.3993 (0.0000)
L-squared = 89.0176 (0.0000)
Cressie-Read = 85.5560 (0.0000)
Dissimilarity index = 0.0406
Degrees of freedom = 7
Log-likelihood = -2260.05027
Number of parameters = 8 (+1)
Sample size = 1402.0
BIC(L-squared) = 38.2980
AIC(L-squared) = 75.0176
BIC(log-likelihood) = 4578.0658
AIC(log-likelihood) = 4536.1005
WARNING: no information is provided on identification of parameters
*** LATENT CLASS OUTPUT ***
X 1 X 2 X 3 X 4 X 5
0.0156 0.0046 0.3691 0.3962 0.2145
W 1 1.0000 0.1732 0.1041 0.0250 0.0068
W 2 0.0000 0.8268 0.8959 0.9750 0.9932
A 1 1.0000 0.8268 0.1041 0.0250 0.0068
A 2 0.0000 0.1732 0.8959 0.9750 0.9932
I 1 1.0000 0.8268 0.8959 0.0250 0.0068
I 2 0.0000 0.1732 0.1041 0.9750 0.9932
V 1 1.0000 0.8268 0.8959 0.9750 0.0068
V 2 0.0000 0.1732 0.1041 0.0250 0.9932
Lazarsfeld's latent distance model:
lat 1
man 4
dim 5 2 2 2 2
lab X W A I V
mod X
W|X eq2
A|X eq2
I|X eq2
V|X eq2
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
des [ 1 0 1 0 1 0 1 0 0 1
2 0 2 0 2 0 0 3 0 3
4 0 4 0 0 5 0 5 0 5
6 0 0 6 0 6 0 6 0 6]
sta W|X [.3 .7 .3 .7 .3 .7 .3 .7 .3 .7]
sta A|X [.3 .7 .3 .7 .3 .7 .3 .7 .3 .7]
sta I|X [.3 .7 .3 .7 .3 .7 .3 .7 .3 .7]
sta V|X [.3 .7 .3 .7 .3 .7 .3 .7 .3 .7]
see 12345
*** STATISTICS ***
Number of iterations = 458
Converge criterion = 0.0000009758
Seed random values = 12345
X-squared = 12.3396 (0.0304)
L-squared = 14.7581 (0.0114)
Cressie-Read = 12.9365 (0.0240)
Dissimilarity index = 0.0148
Degrees of freedom = 5
Log-likelihood = -2222.92051
Number of parameters = 10 (+1)
Sample size = 1402.0
BIC(L-squared) = -21.4702
AIC(L-squared) = 4.7581
BIC(log-likelihood) = 4518.2976
AIC(log-likelihood) = 4465.8410
WARNING: no information is provided on identification of parameters
Page 56 Table 4.5
lat 1
man 4
dim 5 2 2 2 2
lab X W A I V
mod X
W|X eq2
A|X eq2
I|X eq2
V|X eq2
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
des [ 1 0 0 1 0 1 0 1 0 1
2 0 2 0 0 3 0 3 0 3
4 0 4 0 4 0 0 5 0 5
6 0 6 0 6 0 6 0 0 6]
*** (CONDITIONAL) PROBABILITIES *** * P(X) * 1 0.0335 2 0.0484 3 0.1551 4 0.4784 5 0.2846
Page 58 Table 4.6
Intrinsically unscalable:
lat 1
man 4
dim 6 2 2 2 2
lab X W A I V
mod X
W|X eq2
A|X eq2
I|X eq2
V|X eq2
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
des [-1 0 0 -1 0 -1 0 -1 0 -1 0 0
-1 0 -1 0 0 -1 0 -1 0 -1 0 0
-1 0 -1 0 -1 0 0 -1 0 -1 0 0
-1 0 -1 0 -1 0 -1 0 0 -1 0 0]
sta W|X [1 0 0 1 0 1 0 1 0 1 .3 .7]
sta A|X [1 0 1 0 0 1 0 1 0 1 .3 .7]
sta I|X [1 0 1 0 1 0 0 1 0 1 .3 .7]
sta V|X [1 0 1 0 1 0 1 0 0 1 .3 .7]
see 12345
*** STATISTICS ***
Number of iterations = 435
Converge criterion = 0.0000009835
Seed random values = 12345
X-squared = 17.5243 (0.0075)
L-squared = 20.5245 (0.0022)
Cressie-Read = 18.0629 (0.0061)
Dissimilarity index = 0.0171
Degrees of freedom = 6
Log-likelihood = -2225.80372
Number of parameters = 9 (+1)
Sample size = 1402.0
BIC(L-squared) = -22.9495
AIC(L-squared) = 8.5245
BIC(log-likelihood) = 4516.8183
AIC(log-likelihood) = 4469.6074
WARNING: no information is provided on identification of parameters
Proctor-Goodman:
lat 1
man 4
dim 6 2 2 2 2
lab X W A I V
mod X
W|X eq2
A|X eq2
I|X eq2
V|X eq2
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
des [1 0 0 1 0 1 0 1 0 1 0 0
1 0 1 0 0 1 0 1 0 1 0 0
1 0 1 0 1 0 0 1 0 1 0 0
1 0 1 0 1 0 1 0 0 1 0 0]
*** STATISTICS ***
Number of iterations = 218
Converge criterion = 0.0000009647
Seed random values = 3551
X-squared = 16.2441 (0.0062)
L-squared = 20.6331 (0.0010)
Cressie-Read = 17.1663 (0.0042)
Dissimilarity index = 0.0164
Degrees of freedom = 5
Log-likelihood = -2225.85802
Number of parameters = 10 (+1)
Sample size = 1402.0
BIC(L-squared) = -15.5952
AIC(L-squared) = 10.6331
BIC(log-likelihood) = 4524.1726
AIC(log-likelihood) = 4471.7160
WARNING: no information is provided on identification of parameters
Biform scale:
NOTE: The values for chi-squared and L-squared are slightly different from
those shown in the text. We do not know why they are different.
lat 1
man 4
dim 7 2 2 2 2
lab X W A I V
mod X
W|X eq2
A|X eq2
I|X eq2
V|X eq2
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
des [-1 0 0 -1 0 -1 0 -1 0 -1 0 -1 0 0
-1 0 -1 0 0 -1 0 -1 0 -1 0 -1 0 0
-1 0 -1 0 -1 0 0 -1 0 -1 -1 0 0 0
-1 0 -1 0 -1 0 -1 0 0 -1 0 -1 0 0]
sta W|X [1 0 0 1 0 1 0 1 0 1 0 1 .3 .7]
sta A|X [1 0 1 0 0 1 0 1 0 1 0 1 .3 .7]
sta I|X [1 0 1 0 1 0 0 1 0 1 1 0 .3 .7]
sta V|X [1 0 1 0 1 0 1 0 0 1 0 1 .3 .7]
*** STATISTICS ***
Number of iterations = 1114
Converge criterion = 0.0000009976
Seed random values = 4607
X-squared = 5.5992 (0.3472)
L-squared = 6.7613 (0.2390)
Cressie-Read = 5.8294 (0.3232)
Dissimilarity index = 0.0060
Degrees of freedom = 5
Log-likelihood = -2218.92215
Number of parameters = 10 (+1)
Sample size = 1402.0
BIC(L-squared) = -29.4669
AIC(L-squared) = -3.2387
BIC(log-likelihood) = 4510.3009
AIC(log-likelihood) = 4457.8443
WARNING: no information is provided on identification of parameters
Birform scale with Type 2 excluded:
lat 1
man 4
dim 6 2 2 2 2
lab X W A I V
mod X
W|X eq2
A|X eq2
I|X eq2
V|X eq2
dat [27 0
2 0
16 0
4 1
40 3
32 2
339 83
543 310]
des [-1 0 0 -1 0 -1 0 -1 0 -1 0 0
-1 0 0 -1 0 -1 0 -1 0 -1 0 0
-1 0 -1 0 0 -1 -1 0 0 -1 0 0
-1 0 -1 0 -1 0 0 -1 0 -1 0 0]
sta W|X [1 0 0 1 0 1 0 1 0 1 .3 .7]
sta A|X [1 0 0 1 0 1 0 1 0 1 .3 .7]
sta I|X [1 0 1 0 0 1 1 0 0 1 .3 .7]
sta V|X [1 0 1 0 1 0 0 1 0 1 .3 .7]
see 1247
ite 5000
*** STATISTICS ***
Number of iterations = 1122
Converge criterion = 0.0000009996
Seed random values = 1247
X-squared = 5.5992 (0.4695)
L-squared = 6.7613 (0.3435)
Cressie-Read = 5.8294 (0.4426)
Dissimilarity index = 0.0060
Degrees of freedom = 6
Log-likelihood = -2218.92215
Number of parameters = 9 (+1)
Sample size = 1402.0
BIC(L-squared) = -36.7126
AIC(L-squared) = -5.2387
BIC(log-likelihood) = 4503.0552
AIC(log-likelihood) = 4455.8443
WARNING: no information is provided on identification of parameters
Page 70 Table 5.2
NOTE: The code for this model (H0) is given immediately below for the null hypothesis on page 73.
*** (CONDITIONAL) PROBABILITIES *** * P(X|G) * 1 | 1 0.6208 1 | 2 0.3966 2 | 1 0.1723 2 | 2 0.4416 3 | 1 0.2070 3 | 2 0.1619 * P(P|XG) * 1 | 1 1 0.8881 2 | 1 1 0.0532 3 | 1 1 0.0587 1 | 1 2 0.9045 2 | 1 2 0.0474 3 | 1 2 0.0482 1 | 2 1 0.1427 2 | 2 1 0.2246 3 | 2 1 0.6327 1 | 2 2 0.8641 2 | 2 2 0.0855 3 | 2 2 0.0504 1 | 3 1 0.9117 2 | 3 1 0.0716 3 | 3 1 0.0167 1 | 3 2 0.1122 2 | 3 2 0.1758 3 | 3 2 0.7120 * P(A|XG) * 1 | 1 1 0.6130 2 | 1 1 0.3870 1 | 1 2 0.6239 2 | 1 2 0.3761 1 | 2 1 0.0313 2 | 2 1 0.9687 1 | 2 2 0.5239 2 | 2 2 0.4761 1 | 3 1 0.6478 2 | 3 1 0.3522 1 | 3 2 0.0000 * 2 | 3 2 1.0000 * * P(U|XG) * 1 | 1 1 1.0000 * 2 | 1 1 0.0000 * 1 | 1 2 0.4049 2 | 1 2 0.5951 1 | 2 1 0.7531 2 | 2 1 0.2469 1 | 2 2 0.9991 2 | 2 2 0.0009 1 | 3 1 0.3131 2 | 3 1 0.6869 1 | 3 2 0.6776 2 | 3 2 0.3224 * P(C|XG) * 1 | 1 1 0.9431 2 | 1 1 0.0569 3 | 1 1 0.0000 * 1 | 1 2 0.5951 2 | 1 2 0.3370 3 | 1 2 0.0680 1 | 2 1 0.6410 2 | 2 1 0.2561 3 | 2 1 0.1030 1 | 2 2 0.9964 2 | 2 2 0.0000 3 | 2 2 0.0036 1 | 3 1 0.6897 2 | 3 1 0.2553 3 | 3 1 0.0550 1 | 3 2 0.6337 2 | 3 2 0.2525 3 | 3 2 0.1138
Page 73 Table 5.3
Unrestricted, heterogeneous T-class model (H0):
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G
P|XG
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 0 0 0 0 0 0 0 0 0 0 -1 0
0 -1 0 0 0 0 0 0 0 0 0 0
0 0 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
sta A|XG [.6 .4 .6 .4 .05 .95 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 .6 .4 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .1 .1 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 1727
Converge criterion = 0.0000009998
Seed random values = 3375
X-squared = 39.2424 (0.2102)
L-squared = 39.6732 (0.1969)
Cressie-Read = 38.6924 (0.2281)
Dissimilarity index = 0.0336
Degrees of freedom = 33
Log-likelihood = -4853.70192
Number of parameters = 37 (+2)
Sample size = 1649.0
BIC(L-squared) = -204.7883
AIC(L-squared) = -26.3268
BIC(log-likelihood) = 9981.4970
AIC(log-likelihood) = 9781.4038
WARNING: no information is provided on identification of parameters
Partial homogeneity models:
H1:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G
P|XG
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 0 0 0 0 -1 0 0 0 0 0 -1 0
0 -1 0 0 0 0 0 -1 0 0 0 0
0 0 -1 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 381
Converge criterion = 0.0000009909
Seed random values = 3375
X-squared = 40.1875 (0.2900)
L-squared = 39.9460 (0.2991)
Cressie-Read = 39.4078 (0.3200)
Dissimilarity index = 0.0342
Degrees of freedom = 36
Log-likelihood = -4853.83829
Number of parameters = 34 (+2)
Sample size = 1649.0
BIC(L-squared) = -226.7393
AIC(L-squared) = -32.0540
BIC(log-likelihood) = 9959.5460
AIC(log-likelihood) = 9775.6766
WARNING: no information is provided on identification of parameters
H2:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 1 0 0 2 0 0 3 0 0 1 0 0 2 0 0 3 0 0
0 0 0 0 -1 0 0 0 0 0 -1 0
0 -1 0 0 0 0 0 -1 0 0 0 0
0 0 -1 0 0 0 4 5 0 0 0 -1 0 0 0 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 531
Converge criterion = 0.0000009965
Seed random values = 3375
X-squared = 40.4424 (0.4952)
L-squared = 40.1704 (0.5073)
Cressie-Read = 39.6305 (0.5315)
Dissimilarity index = 0.0339
Degrees of freedom = 41
Log-likelihood = -4853.95049
Number of parameters = 29 (+2)
Sample size = 1649.0
BIC(L-squared) = -263.5545
AIC(L-squared) = -41.8296
BIC(log-likelihood) = 9922.7308
AIC(log-likelihood) = 9765.9010
WARNING: no information is provided on identification of parameters
H3:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 1 7 0 2 8 0 3 0 0 1 7 0 2 8 0 3 0 0
0 0 6 0 -1 0 0 0 6 0 -1 0
0 -1 0 0 0 0 0 -1 0 0 0 0
0 0 -1 0 0 9 4 5 0 0 0 -1 0 0 9 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 204
Converge criterion = 0.0000009844
Seed random values = 3375
X-squared = 43.3219 (0.5432)
L-squared = 42.8310 (0.5643)
Cressie-Read = 42.3756 (0.5838)
Dissimilarity index = 0.0349
Degrees of freedom = 45
Log-likelihood = -4855.28080
Number of parameters = 25 (+2)
Sample size = 1649.0
BIC(L-squared) = -290.5256
AIC(L-squared) = -47.1690
BIC(log-likelihood) = 9895.7597
AIC(log-likelihood) = 9760.5616
WARNING: no information is provided on identification of parameters
H4:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 1 7 0 2 8 0 3 10 0 1 7 0 2 8 0 3 10 0
0 0 6 0 -1 0 0 0 6 0 -1 0
0 -1 0 0 13 0 0 -1 0 0 13 0
0 0 -1 0 0 9 4 5 0 0 0 -1 0 0 9 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 201
Converge criterion = 0.0000009670
Seed random values = 3375
X-squared = 44.0410 (0.5959)
L-squared = 43.9905 (0.5980)
Cressie-Read = 43.1947 (0.6309)
Dissimilarity index = 0.0351
Degrees of freedom = 47
Log-likelihood = -4855.86056
Number of parameters = 23 (+2)
Sample size = 1649.0
BIC(L-squared) = -304.1819
AIC(L-squared) = -50.0095
BIC(log-likelihood) = 9882.1034
AIC(log-likelihood) = 9757.7211
WARNING: no information is provided on identification of parameters
H5:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 1 7 0 2 8 0 3 10 0 1 7 0 2 8 0 3 10 0
0 0 6 0 -1 0 0 0 6 0 -1 0
0 -1 0 0 13 0 0 -1 0 0 13 0
0 0 -1 15 0 9 4 5 0 0 0 -1 15 0 9 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 263
Converge criterion = 0.0000009951
Seed random values = 3375
X-squared = 45.9464 (0.5574)
L-squared = 45.9171 (0.5586)
Cressie-Read = 45.1164 (0.5917)
Dissimilarity index = 0.0389
Degrees of freedom = 48
Log-likelihood = -4856.82383
Number of parameters = 22 (+2)
Sample size = 1649.0
BIC(L-squared) = -309.6633
AIC(L-squared) = -50.0829
BIC(log-likelihood) = 9876.6220
AIC(log-likelihood) = 9757.6477
WARNING: no information is provided on identification of parameters
H6:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 1 7 0 2 8 0 3 10 0 1 7 0 2 8 0 3 10 0
0 0 6 0 -1 0 0 0 6 0 -1 0
0 -1 0 0 13 0 0 -1 0 0 13 0
14 0 -1 15 0 9 4 5 0 14 0 -1 15 0 9 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 263
Converge criterion = 0.0000009681
Seed random values = 3375
X-squared = 46.6283 (0.5698)
L-squared = 47.4200 (0.5373)
Cressie-Read = 46.1117 (0.5909)
Dissimilarity index = 0.0386
Degrees of freedom = 49
Log-likelihood = -4857.57532
Number of parameters = 21 (+2)
Sample size = 1649.0
BIC(L-squared) = -315.5682
AIC(L-squared) = -50.5800
BIC(log-likelihood) = 9870.7171
AIC(log-likelihood) = 9757.1506
WARNING: no information is provided on identification of parameters
H7:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 1 7 0 2 8 0 3 10 0 1 7 0 2 8 0 3 10 0
0 0 6 0 -1 0 0 0 6 0 -1 0
0 -1 12 0 13 0 0 -1 12 0 13 0
14 0 -1 15 0 9 4 5 0 14 0 -1 15 0 9 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 176
Converge criterion = 0.0000009728
Seed random values = 3375
X-squared = 46.5545 (0.6124)
L-squared = 47.4328 (0.5770)
Cressie-Read = 46.0796 (0.6314)
Dissimilarity index = 0.0386
Degrees of freedom = 50
Log-likelihood = -4857.58169
Number of parameters = 20 (+2)
Sample size = 1649.0
BIC(L-squared) = -322.9634
AIC(L-squared) = -52.5672
BIC(log-likelihood) = 9863.3219
AIC(log-likelihood) = 9755.1634
WARNING: no information is provided on identification of parameters
H8:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 1 7 0 2 8 0 3 10 0 1 7 0 2 8 0 3 10 0
11 0 6 0 -1 0 11 0 6 0 -1 0
0 -1 12 0 13 0 0 -1 12 0 13 0
14 0 -1 15 0 9 4 5 0 14 0 -1 15 0 9 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 173
Converge criterion = 0.0000009618
Seed random values = 3375
X-squared = 49.0210 (0.5526)
L-squared = 49.8224 (0.5205)
Cressie-Read = 48.5005 (0.5735)
Dissimilarity index = 0.0472
Degrees of freedom = 51
Log-likelihood = -4858.77648
Number of parameters = 19 (+2)
Sample size = 1649.0
BIC(L-squared) = -327.9818
AIC(L-squared) = -52.1776
BIC(log-likelihood) = 9858.3035
AIC(log-likelihood) = 9755.5530
WARNING: no information is provided on identification of parameters
H9:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 1 7 0 1 7 0 3 10 0 1 7 0 1 7 0 3 10 0
11 0 11 0 -1 0 11 0 11 0 -1 0
0 -1 12 0 13 0 0 -1 12 0 13 0
14 0 -1 15 0 9 4 5 0 14 0 -1 15 0 9 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 3375
*** STATISTICS ***
Number of iterations = 163 Converge criterion = 0.0000009129 Seed random values = 3375
X-squared = 50.5866 (0.6068) L-squared = 51.7339 (0.5623) Cressie-Read = 50.0778 (0.6264) Dissimilarity index = 0.0462 Degrees of freedom = 54 Log-likelihood = -4859.73223 Number of parameters = 17 (+1) Sample size = 1649.0 BIC(L-squared) = -348.2941 AIC(L-squared) = -56.2661 BIC(log-likelihood) = 9845.3992 AIC(log-likelihood) = 9753.4645
H10:
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G eq2
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 0 0 20 0 0 20
1 7 0 1 7 0 3 10 0 1 7 0 1 7 0 3 10 0
11 0 11 0 -1 0 11 0 11 0 -1 0
0 -1 12 0 13 0 0 -1 12 0 13 0
14 0 -1 15 0 9 4 5 0 14 0 -1 15 0 9 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 2377
*** STATISTICS ***
Number of iterations = 172
Converge criterion = 0.0000009838
Seed random values = 2377
X-squared = 51.6807 (0.6022)
L-squared = 52.2970 (0.5786)
Cressie-Read = 50.9835 (0.6288)
Dissimilarity index = 0.0472
Degrees of freedom = 55
Log-likelihood = -4860.01380
Number of parameters = 16 (+1)
Sample size = 1649.0
BIC(L-squared) = -355.1388
AIC(L-squared) = -57.7030
BIC(log-likelihood) = 9838.5544
AIC(log-likelihood) = 9752.0276
Restricted, complete homogeneity model. There is a difference in terms of
degrees of freedom and the parameter estimates. We believe that the model
specified here is correct.
lat 1
man 5
dim 3 2 3 2 2 3
lab X G P A U C
mod
X|G eq2
P|XG eq2
A|XG eq2
U|XG eq2
C|XG eq2
rec 64
rco
des [ 0 21 20 0 21 20
1 7 0 1 7 0 3 10 0 1 7 0 1 7 0 3 10 0
11 0 11 0 -1 0 11 0 11 0 -1 0
0 -1 12 0 13 0 0 -1 12 0 13 0
14 0 -1 15 0 9 4 5 0 14 0 -1 15 0 9 4 5 0]
sta A|XG [.6 .4 .6 .4 0 1 .6 .4 .7 .3 0 1]
sta U|XG [ 1 0 .6 .4 .6 .4 1 0 .6 .4 .6 .4]
sta C|XG [.8 .2 0 .6 .2 .2 .6 .2 .2 .8 .2 0 .6 .2 .2 .6 .2 .2]
dat [
1 1 1 1 1 419
1 1 1 1 2 35
1 1 1 1 3 2
1 1 1 2 1 71
1 1 1 2 2 25
1 1 1 2 3 5
1 1 2 1 1 270
1 1 2 1 2 25
1 1 2 1 3 4
1 1 2 2 1 42
1 1 2 2 2 16
1 1 2 2 3 5
1 2 1 1 1 23
1 2 1 1 2 4
1 2 1 1 3 1
1 2 1 2 1 6
1 2 1 2 2 2
1 2 2 1 1 43
1 2 2 1 2 9
1 2 2 1 3 2
1 2 2 2 1 9
1 2 2 2 2 3
1 2 2 2 3 2
1 3 1 1 1 26
1 3 1 1 2 3
1 3 1 2 1 1
1 3 1 2 2 2
1 3 2 1 1 85
1 3 2 1 2 23
1 3 2 1 3 6
1 3 2 2 1 13
1 3 2 2 2 12
1 3 2 2 3 8
2 1 1 1 1 117
2 1 1 1 2 14
2 1 1 1 3 3
2 1 1 2 1 34
2 1 1 2 2 19
2 1 1 2 3 5
2 1 2 1 1 95
2 1 2 1 2 10
2 1 2 1 3 3
2 1 2 2 1 23
2 1 2 2 2 14
2 1 2 2 3 2
2 2 1 1 1 7
2 2 1 1 2 1
2 2 1 2 1 3
2 2 1 2 2 1
2 2 2 1 1 19
2 2 2 1 2 1
2 2 2 1 3 2
2 2 2 2 1 2
2 2 2 2 2 1
2 2 2 2 3 1
2 3 1 1 1 6
2 3 1 2 1 3
2 3 1 2 2 1
2 3 2 1 1 30
2 3 2 1 2 9
2 3 2 1 3 1
2 3 2 2 1 9
2 3 2 2 2 7
2 3 2 2 3 4]
ite 5000
see 2377
*** STATISTICS ***
Number of iterations = 343
Converge criterion = 0.0000009706
Seed random values = 2377
X-squared = 74.9221 (0.0465)
L-squared = 74.7915 (0.0475)
Cressie-Read = 73.9253 (0.0545)
Dissimilarity index = 0.0644
Degrees of freedom = 56
Log-likelihood = -4871.26103
Number of parameters = 14 (+2)
Sample size = 1649.0
BIC(L-squared) = -340.0523
AIC(L-squared) = -37.2085
BIC(log-likelihood) = 9846.2330
AIC(log-likelihood) = 9770.5221
Page 76 Table 5.4
NOTE: The code for this is given above for model H10.
*** (CONDITIONAL) PROBABILITIES *** * P(X|G) * 1 | 1 0.6146 1 | 2 0.3765 2 | 1 0.1588 2 | 2 0.4647 3 | 1 0.2266 3 | 2 0.1588 * P(P|XG) * 1 | 1 1 0.8881 2 | 1 1 0.0597 3 | 1 1 0.0522 1 | 1 2 0.8881 2 | 1 2 0.0597 3 | 1 2 0.0522 1 | 2 1 0.0997 2 | 2 1 0.2258 3 | 2 1 0.6745 1 | 2 2 0.8881 2 | 2 2 0.0597 3 | 2 2 0.0522 1 | 3 1 0.8881 2 | 3 1 0.0597 3 | 3 1 0.0522 1 | 3 2 0.0997 2 | 3 2 0.2258 3 | 3 2 0.6745 * P(A|XG) * 1 | 1 1 0.6049 2 | 1 1 0.3951 1 | 1 2 0.6049 2 | 1 2 0.3951 1 | 2 1 0.0000 * 2 | 2 1 1.0000 * 1 | 2 2 0.6049 2 | 2 2 0.3951 1 | 3 1 0.6049 2 | 3 1 0.3951 1 | 3 2 0.0000 * 2 | 3 2 1.0000 * * P(U|XG) * 1 | 1 1 1.0000 * 2 | 1 1 0.0000 * 1 | 1 2 0.3511 2 | 1 2 0.6489 1 | 2 1 0.7497 2 | 2 1 0.2503 1 | 2 2 1.0000 * 2 | 2 2 0.0000 * 1 | 3 1 0.3511 2 | 3 1 0.6489 1 | 3 2 0.7497 2 | 3 2 0.2503 * P(C|XG) * 1 | 1 1 0.9498 2 | 1 1 0.0502 3 | 1 1 0.0000 * 1 | 1 2 0.6483 2 | 1 2 0.2862 3 | 1 2 0.0655 1 | 2 1 0.6535 2 | 2 1 0.2426 3 | 2 1 0.1039 1 | 2 2 0.9498 2 | 2 2 0.0502 3 | 2 2 0.0000 * 1 | 3 1 0.6483 2 | 3 1 0.2862 3 | 3 1 0.0655 1 | 3 2 0.6535 2 | 3 2 0.2426 3 | 3 2 0.1039
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