Multivariate Analysis
Latent Class & Mixture Models Using Latent Gold
2 & 3 Class Latent Mixture Models Using Latent Gold
| File name: |
D:\latent_gold\hsb6a.sav |
| File size: |
51508 bytes |
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| File date: |
2005-Aug-04 |
01:01:26 PM |
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LL |
BIC(LL) |
Npar |
Class.Err. |
| Model1 |
2-Cluster |
-10458.3884 |
21051.1123 |
21 |
0.0401 |
| Model2 |
3-Cluster |
-10268.4203 |
20741.5423 |
32 |
0.0735 |
| Model3 |
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Model1 - LL = -10458.3884
| 2-Cluster Model |
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| Number of cases |
600 |
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| Number of parameters (Npar) |
21 |
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| Activated Constraints |
0 |
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| Random Seed |
45021 |
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| Best Start Seed |
797209 |
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| Log-likelihood Statistics |
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| Log-likelihood (LL) |
-10458.3884 |
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| Log-prior |
0.0000 |
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| Log-posterior |
-10458.3884 |
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| BIC (based on LL) |
21051.1123 |
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| AIC (based on LL) |
20958.7768 |
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| AIC3 (based on LL) |
20979.7768 |
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| CAIC (based on LL) |
21072.1123 |
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| Classification Statistics |
Clusters |
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| Classification errors |
0.0401 |
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| Reduction of errors (Lambda) |
0.9113 |
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| Entropy R-squared |
0.8595 |
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| Standard R-squared |
0.8815 |
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| Classification log-likelihood |
-10516.4182 |
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| AWE |
21364.5074 |
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| Classification Table |
Modal |
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| Probabilistic |
Cluster1 |
Cluster2 |
Total |
| Cluster1 |
316.7871 |
11.8474 |
328.6344 |
| Cluster2 |
12.2129 |
259.1526 |
271.3656 |
| Total |
329.0000 |
271.0000 |
600.0000 |
Parameters
| Models for Indicators |
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Cluster1 |
Cluster2 |
Wald |
p-value |
Rē |
| read |
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7.5328 |
-7.5328 |
668.2344 |
2.4e-147 |
0.5518 |
| write |
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6.7741 |
-6.7741 |
475.5821 |
2.0e-105 |
0.4814 |
| math |
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6.4485 |
-6.4485 |
498.2408 |
2.3e-110 |
0.4656 |
| sci |
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6.7204 |
-6.7204 |
458.6066 |
9.7e-102 |
0.4758 |
| ss |
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5.9439 |
-5.9439 |
293.8590 |
7.2e-66 |
0.3593 |
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| Intercepts |
Overall |
Wald |
p-value |
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| read |
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51.1828 |
17842.7797 |
1.8e-3877 |
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| write |
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51.7383 |
18520.3764 |
1.3e-4024 |
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| math |
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51.2335 |
21025.8003 |
1.1e-4568 |
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| sci |
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51.1219 |
18189.2511 |
1.1e-3952 |
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| ss |
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51.4783 |
17642.5081 |
5.7e-3834 |
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| Error Variances |
Cluster1 |
Cluster2 |
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| read |
53.4316 |
36.2780 |
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| write |
35.0947 |
65.7859 |
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| math |
59.0152 |
33.0804 |
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| sci |
44.6676 |
54.9112 |
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| ss |
62.3951 |
62.4693 |
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| Model for Clusters |
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| Intercept |
Cluster1 |
Cluster2 |
Wald |
p-value |
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0.0957 |
-0.0957 |
3.1173 |
0.077 |
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Loadings
| Loadings |
Clusters |
Rē |
| read |
0.7428 |
0.5518 |
| write |
0.6939 |
0.4814 |
| math |
0.6824 |
0.4656 |
| sci |
0.6898 |
0.4758 |
| ss |
0.5994 |
0.3593 |
Profile
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Cluster1 |
Cluster2 |
| Cluster Size |
0.5477 |
0.4523 |
| Indicators |
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| read |
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| Mean |
58.7157 |
43.6500 |
| write |
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| Mean |
58.5124 |
44.9641 |
| math |
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| Mean |
57.6820 |
44.7850 |
| sci |
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| Mean |
57.8423 |
44.4015 |
| ss |
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| Mean |
57.4222 |
45.5345 |
ProbMeans
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Cluster1 |
Cluster2 |
| Overall |
0.5477 |
0.4523 |
| Indicators |
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| read |
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| 28.30 - 41.60 |
0.0291 |
0.9709 |
| 42.10 - 48.40 |
0.1952 |
0.8048 |
| 49.50 - 54.30 |
0.5776 |
0.4224 |
| 54.80 - 62.20 |
0.8959 |
0.1041 |
| 62.70 - 76 |
0.9902 |
0.0098 |
| write |
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| 25.50 - 41.70 |
0.0238 |
0.9762 |
| 43 - 50.80 |
0.2799 |
0.7201 |
| 51.50 - 56.70 |
0.6224 |
0.3776 |
| 57.30 - 61.20 |
0.8536 |
0.1464 |
| 61.90 - 67.10 |
0.9586 |
0.0414 |
| math |
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| 31.80 - 42.60 |
0.0865 |
0.9135 |
| 42.80 - 48.30 |
0.2316 |
0.7684 |
| 48.50 - 53.90 |
0.5696 |
0.4304 |
| 54.30 - 60.40 |
0.8515 |
0.1485 |
| 60.50 - 75.50 |
0.9918 |
0.0082 |
| sci |
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| 26 - 41.70 |
0.0402 |
0.9598 |
| 42.30 - 49.30 |
0.2926 |
0.7074 |
| 49.80 - 55.30 |
0.6065 |
0.3935 |
| 55.80 - 60.10 |
0.8301 |
0.1699 |
| 60.70 - 74.20 |
0.9679 |
0.0321 |
| ss |
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| 25.70 - 44.30 |
0.1188 |
0.8812 |
| 45.60 - 49.30 |
0.2749 |
0.7251 |
| 50.60 - 53.10 |
0.4996 |
0.5004 |
| 55.60 - 60.50 |
0.7641 |
0.2359 |
| 61.80 - 70.50 |
0.9903 |
0.0097 |
Bivariate Residuals
| Indicators |
read |
write |
math |
sci |
ss |
| read |
. |
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| write |
18.5943 |
. |
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| math |
36.1426 |
30.8713 |
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| sci |
41.4063 |
8.7855 |
35.2455 |
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| ss |
22.2074 |
25.9209 |
13.8318 |
10.6332 |
. |
Model2 - LL = -10268.4203
| 3-Cluster Model |
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| Number of cases |
600 |
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| Number of parameters (Npar) |
32 |
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| Activated Constraints |
0 |
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| Random Seed |
76271 |
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| Best Start Seed |
2398072 |
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| Log-likelihood Statistics |
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| Log-likelihood (LL) |
-10268.4203 |
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| Log-prior |
0.0000 |
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| Log-posterior |
-10268.4203 |
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| BIC (based on LL) |
20741.5423 |
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| AIC (based on LL) |
20600.8405 |
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| AIC3 (based on LL) |
20632.8405 |
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| CAIC (based on LL) |
20773.5423 |
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| Classification Statistics |
Clusters |
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| Classification errors |
0.0735 |
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| Reduction of errors (Lambda) |
0.8688 |
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| Entropy R-squared |
0.8341 |
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| Standard R-squared |
0.8328 |
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| Classification log-likelihood |
-10374.6353 |
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| AWE |
21254.6740 |
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| Classification Table |
Modal |
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| Probabilistic |
Cluster1 |
Cluster2 |
Cluster3 |
Total |
| Cluster1 |
239.3894 |
12.0656 |
12.4360 |
263.8910 |
| Cluster2 |
9.4238 |
185.9344 |
0.0000 |
195.3582 |
| Cluster3 |
10.1868 |
0.0000 |
130.5640 |
140.7508 |
| Total |
259.0000 |
198.0000 |
143.0000 |
600.0000 |
Parameters
| Models for Indicators |
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Cluster1 |
Cluster2 |
Cluster3 |
Wald |
p-value |
Rē |
| read |
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0.2791 |
-11.1234 |
10.8443 |
862.6455 |
4.8e-188 |
0.6575 |
| write |
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1.2388 |
-10.1057 |
8.8669 |
714.9207 |
5.7e-156 |
0.5498 |
| math |
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-0.3042 |
-9.7332 |
10.0374 |
742.6438 |
5.5e-162 |
0.6060 |
| sci |
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0.9364 |
-10.3528 |
9.4164 |
750.1627 |
1.3e-163 |
0.5903 |
| ss |
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-0.0292 |
-8.9554 |
8.9846 |
496.7305 |
1.4e-108 |
0.4554 |
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| Intercepts |
Overall |
Wald |
p-value |
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| read |
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52.8569 |
17621.4698 |
2.1e-3829 |
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| write |
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53.0503 |
22441.9197 |
3.4e-4876 |
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| math |
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52.7973 |
20211.2079 |
8.7e-4392 |
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| sci |
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52.5134 |
20711.6466 |
1.8e-4500 |
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| ss |
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52.8667 |
19140.2139 |
3.3e-4159 |
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| Error Variances |
Cluster1 |
Cluster2 |
Cluster3 |
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| read |
40.4548 |
27.0984 |
35.3357 |
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| write |
43.6435 |
61.8164 |
13.6254 |
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| math |
39.1420 |
25.0700 |
40.4546 |
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| sci |
41.9849 |
42.3877 |
26.7052 |
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| ss |
62.8100 |
54.6521 |
32.5745 |
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| Model for Clusters |
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| Intercept |
Cluster1 |
Cluster2 |
Cluster3 |
Wald |
p-value |
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0.3097 |
0.0090 |
-0.3188 |
20.3245 |
3.9e-5 |
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Loadings
| Loadings |
Clusters |
Rē |
| read |
0.8108 |
0.6575 |
| write |
0.7415 |
0.5498 |
| math |
0.7784 |
0.6060 |
| sci |
0.7683 |
0.5903 |
| ss |
0.6749 |
0.4554 |
Profile
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Cluster1 |
Cluster2 |
Cluster3 |
| Cluster Size |
0.4398 |
0.3256 |
0.2346 |
| Indicators |
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| read |
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| Mean |
53.1360 |
41.7335 |
63.7012 |
| write |
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| Mean |
54.2891 |
42.9446 |
61.9173 |
| math |
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| Mean |
52.4930 |
43.0641 |
62.8347 |
| sci |
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| Mean |
53.4498 |
42.1606 |
61.9298 |
| ss |
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| Mean |
52.8375 |
43.9113 |
61.8514 |
ProbMeans
|
Cluster1 |
Cluster2 |
Cluster3 |
| Overall |
0.4398 |
0.3256 |
0.2346 |
| Indicators |
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| read |
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| 28.30 - 41.60 |
0.0958 |
0.9042 |
0.0000 |
| 42.10 - 48.40 |
0.4242 |
0.5646 |
0.0112 |
| 49.50 - 54.30 |
0.7827 |
0.1534 |
0.0640 |
| 54.80 - 62.20 |
0.7062 |
0.0254 |
0.2684 |
| 62.70 - 76 |
0.2289 |
0.0001 |
0.7711 |
| write |
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| 25.50 - 41.70 |
0.1127 |
0.8873 |
0.0000 |
| 43 - 50.80 |
0.5027 |
0.4965 |
0.0008 |
| 51.50 - 56.70 |
0.7088 |
0.1625 |
0.1288 |
| 57.30 - 61.20 |
0.5305 |
0.0906 |
0.3789 |
| 61.90 - 67.10 |
0.3201 |
0.0196 |
0.6603 |
| math |
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| 31.80 - 42.60 |
0.1672 |
0.8324 |
0.0004 |
| 42.80 - 48.30 |
0.3985 |
0.5809 |
0.0206 |
| 48.50 - 53.90 |
0.7273 |
0.1882 |
0.0846 |
| 54.30 - 60.40 |
0.6639 |
0.0361 |
0.3000 |
| 60.50 - 75.50 |
0.2373 |
0.0002 |
0.7625 |
| sci |
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| 26 - 41.70 |
0.1215 |
0.8784 |
0.0001 |
| 42.30 - 49.30 |
0.4724 |
0.5170 |
0.0106 |
| 49.80 - 55.30 |
0.7154 |
0.1669 |
0.1176 |
| 55.80 - 60.10 |
0.6057 |
0.0703 |
0.3240 |
| 60.70 - 74.20 |
0.3223 |
0.0019 |
0.6757 |
| ss |
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| 25.70 - 44.30 |
0.2524 |
0.7475 |
0.0002 |
| 45.60 - 49.30 |
0.4080 |
0.5689 |
0.0232 |
| 50.60 - 53.10 |
0.6012 |
0.3293 |
0.0695 |
| 55.60 - 60.50 |
0.5637 |
0.0996 |
0.3367 |
| 61.80 - 70.50 |
0.2497 |
0.0001 |
0.7502 |
Bivariate Residuals
| Indicators |
read |
write |
math |
sci |
ss |
| read |
. |
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| write |
1.3962 |
. |
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| math |
4.8516 |
4.9237 |
. |
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| sci |
7.5766 |
1.3345 |
4.2230 |
. |
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| ss |
3.1629 |
8.3389 |
0.6561 |
0.5608 |
. |
Ed231A Page
UCLA Department of Education
Phil Ender, 24apr03