Jason T.
Newsom, Richard N. Jones, & Scott M. Hofer.
Longitudinal
data analysis: A practical guide for researchers in aging, health, and social
sciences
CHAPTER 9
Jones R.
Table 9.1 Results of
Unconditional and Conditional Latent Growth Curve Models of
Change in Mini-Mental
State Examination Performance in the Hispanic EPESE
Mm = Mini-Mental state examination
performance
cBage = centered age
cgrs23007 = centered gender
ceds23018 = centered
education
cras23008 = centered
born in US
civs23483 = centered
Spanish interview
UNCONDITIONAL MODEL
Date: Thursday, March 31, 2011
Time: 4:23:15 PM
chpt9unc amos: Thursday, March 31, 2011 4:23 PM
The model is recursive.
Sample size = 2942
Observed, endogenous variables
MM0
MM1
MM2
MM3
MM4
MM5
mm6
mm7
mm8
Unobserved, exogenous variables
ICEPT
SLOPE
E1
E2
E3
E4
E5
E6
E7
E8
E9
Number of variables in your model: |
20 |
Number of observed variables: |
9 |
Number of unobserved variables: |
11 |
Number of exogenous variables: |
11 |
Number of endogenous variables: |
9 |
|
Weights |
Covariances |
Variances |
Means |
Intercepts |
Total |
Fixed |
27 |
0 |
0 |
0 |
0 |
27 |
Labeled |
0 |
0 |
9 |
0 |
0 |
9 |
Unlabeled |
0 |
1 |
2 |
2 |
0 |
5 |
Total |
27 |
1 |
11 |
2 |
0 |
41 |
Number of distinct sample moments: |
54 |
Number of distinct parameters to be estimated: |
6 |
Degrees of freedom (54 - 6): |
48 |
Minimum was achieved
Function of log likelihood = 39289.117
Number of parameters = 6
|
|
|
Estimate |
S.E. |
C.R. |
P |
Label |
MM0 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM0 |
<--- |
SLOPE |
.000 |
|
|
|
|
MM1 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM1 |
<--- |
SLOPE |
1.000 |
|
|
|
|
MM2 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM2 |
<--- |
SLOPE |
2.000 |
|
|
|
|
MM3 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM3 |
<--- |
SLOPE |
3.000 |
|
|
|
|
MM4 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM4 |
<--- |
SLOPE |
4.000 |
|
|
|
|
MM5 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM5 |
<--- |
SLOPE |
5.000 |
|
|
|
|
mm6 |
<--- |
SLOPE |
6.000 |
|
|
|
|
mm7 |
<--- |
SLOPE |
7.000 |
|
|
|
|
mm8 |
<--- |
SLOPE |
8.000 |
|
|
|
|
mm6 |
<--- |
ICEPT |
1.000 |
|
|
|
|
mm7 |
<--- |
ICEPT |
1.000 |
|
|
|
|
mm8 |
<--- |
ICEPT |
1.000 |
|
|
|
|
|
|
|
Estimate |
MM0 |
<--- |
ICEPT |
.691 |
MM0 |
<--- |
SLOPE |
.000 |
MM1 |
<--- |
ICEPT |
.660 |
MM1 |
<--- |
SLOPE |
.112 |
MM2 |
<--- |
ICEPT |
.626 |
MM2 |
<--- |
SLOPE |
.213 |
MM3 |
<--- |
ICEPT |
.590 |
MM3 |
<--- |
SLOPE |
.301 |
MM4 |
<--- |
ICEPT |
.555 |
MM4 |
<--- |
SLOPE |
.378 |
MM5 |
<--- |
ICEPT |
.522 |
MM5 |
<--- |
SLOPE |
.443 |
mm6 |
<--- |
SLOPE |
.500 |
mm7 |
<--- |
SLOPE |
.548 |
mm8 |
<--- |
SLOPE |
.590 |
mm6 |
<--- |
ICEPT |
.490 |
mm7 |
<--- |
ICEPT |
.461 |
mm8 |
<--- |
ICEPT |
.434 |
|
|
|
Estimate |
S.E. |
C.R. |
P |
Label |
ICEPT |
|
|
24.387 |
.090 |
271.125 |
*** |
|
SLOPE |
|
|
-.681 |
.022 |
-31.571 |
*** |
|
|
|
|
Estimate |
S.E. |
C.R. |
P |
Label |
ICEPT |
<--> |
SLOPE |
1.121 |
.112 |
10.007 |
*** |
|
|
|
|
Estimate |
ICEPT |
<--> |
SLOPE |
.505 |
|
|
|
Estimate |
S.E. |
C.R. |
P |
Label |
ICEPT |
|
|
13.054 |
.665 |
19.619 |
*** |
|
SLOPE |
|
|
.377 |
.032 |
11.845 |
*** |
|
E1 |
|
|
14.298 |
.336 |
42.545 |
*** |
V |
E2 |
|
|
14.298 |
.336 |
42.545 |
*** |
V |
E3 |
|
|
14.298 |
.336 |
42.545 |
*** |
V |
E4 |
|
|
14.298 |
.336 |
42.545 |
*** |
V |
E5 |
|
|
14.298 |
.336 |
42.545 |
*** |
V |
E6 |
|
|
14.298 |
.336 |
42.545 |
*** |
V |
E7 |
|
|
14.298 |
.336 |
42.545 |
*** |
V |
E9 |
|
|
14.298 |
.336 |
42.545 |
*** |
V |
E8 |
|
|
14.298 |
.336 |
42.545 |
*** |
V |
Iteration |
|
Negative |
Condition # |
Smallest |
Diameter |
F |
NTries |
Ratio |
0 |
e |
1 |
|
-.178 |
9999.000 |
96282.393 |
0 |
9999.000 |
1 |
e* |
3 |
|
-.930 |
1.268 |
46408.431 |
14 |
.717 |
2 |
e |
3 |
|
-2.832 |
.383 |
43094.619 |
5 |
.660 |
3 |
e |
1 |
|
-1.284 |
.123 |
41608.650 |
5 |
.760 |
4 |
e |
1 |
|
-.132 |
.090 |
41111.767 |
5 |
.715 |
5 |
e* |
0 |
24910.787 |
|
.245 |
40036.034 |
6 |
.830 |
6 |
e |
0 |
1741.184 |
|
.702 |
39722.978 |
3 |
.000 |
7 |
e |
0 |
859.598 |
|
.204 |
39381.903 |
1 |
1.218 |
8 |
e |
0 |
867.571 |
|
.080 |
39299.075 |
1 |
1.177 |
9 |
e |
0 |
862.529 |
|
.023 |
39289.388 |
1 |
1.099 |
10 |
e |
0 |
844.135 |
|
.002 |
39289.118 |
1 |
1.022 |
11 |
e |
0 |
834.756 |
|
.000 |
39289.117 |
1 |
1.001 |
The saturated model was not fitted to the data of at least one group.
For this reason, only the 'function of log likelihood', AIC and BCC are
reported. The likelihood ratio chi square statistic and other fit measures are
not reported.
Model |
NPAR |
CMIN |
Default model |
6 |
39289.117 |
Model |
AIC |
BCC |
BIC |
CAIC |
Default model |
39301.117 |
39301.158 |
|
|
Minimization: |
.047 |
Miscellaneous: |
.296 |
Bootstrap: |
.000 |
Total: |
.343 |
Table 9.1 Results of Unconditional and Conditional Latent
Growth Curve Models of
Change in Mini-Mental
State Examination Performance in the Hispanic EPESE
CONDITIONAL MODEL
Output from this model differs somewhat from the Mplus
and Lisrel output because of minor differences in how
missing data is estimated with FIML. Amos did not print the chi-square for the
model because of low covariance coverage of missing data.
Date: Thursday, March 31, 2011
Time: 4:13:55 PM
chpt9con amos: Thursday, March 31, 2011 4:13 PM
The model is recursive.
Sample size = 2942
Observed, endogenous variables
MM0
MM1
MM2
MM3
MM4
MM5
mm6
mm7
mm8
Observed, exogenous variables
grs23007
eds23018
ivs23483
Bage
ras23008
Unobserved, endogenous variables
ICEPT
SLOPE
Unobserved, exogenous variables
E1
E2
E3
E4
E5
E6
E7
E8
E9
d1
d2
Number of variables in your model: |
27 |
Number of observed variables: |
14 |
Number of unobserved variables: |
13 |
Number of exogenous variables: |
16 |
Number of endogenous variables: |
11 |
|
Weights |
Covariances |
Variances |
Means |
Intercepts |
Total |
Fixed |
29 |
0 |
0 |
0 |
0 |
29 |
Labeled |
0 |
0 |
0 |
0 |
0 |
0 |
Unlabeled |
10 |
11 |
16 |
0 |
2 |
39 |
Total |
39 |
11 |
16 |
0 |
2 |
68 |
Number of distinct sample moments: |
119 |
Number of distinct parameters to be estimated: |
39 |
Degrees of freedom (119 - 39): |
80 |
Minimum was achieved
Function of log likelihood = 57513.708
Number of parameters = 39
|
|
|
Estimate |
S.E. |
C.R. |
P |
Label |
ICEPT |
<--- |
grs23007 |
.024 |
.158 |
.151 |
.880 |
|
SLOPE |
<--- |
grs23007 |
.003 |
.041 |
.080 |
.936 |
|
ICEPT |
<--- |
eds23018 |
.496 |
.022 |
22.571 |
*** |
|
ICEPT |
<--- |
ivs23483 |
.543 |
.207 |
2.627 |
.009 |
|
ICEPT |
<--- |
Bage |
-.191 |
.012 |
-16.030 |
*** |
|
ICEPT |
<--- |
ras23008 |
-.042 |
.166 |
-.254 |
.799 |
|
SLOPE |
<--- |
eds23018 |
-.005 |
.006 |
-.935 |
.350 |
|
SLOPE |
<--- |
ivs23483 |
.038 |
.053 |
.711 |
.477 |
|
SLOPE |
<--- |
Bage |
-.043 |
.003 |
-13.996 |
*** |
|
SLOPE |
<--- |
ras23008 |
.047 |
.043 |
1.092 |
.275 |
|
MM0 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM0 |
<--- |
SLOPE |
.000 |
|
|
|
|
MM1 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM1 |
<--- |
SLOPE |
1.000 |
|
|
|
|
MM2 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM2 |
<--- |
SLOPE |
2.000 |
|
|
|
|
MM3 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM3 |
<--- |
SLOPE |
3.000 |
|
|
|
|
MM4 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM4 |
<--- |
SLOPE |
4.000 |
|
|
|
|
MM5 |
<--- |
ICEPT |
1.000 |
|
|
|
|
MM5 |
<--- |
SLOPE |
5.000 |
|
|
|
|
mm6 |
<--- |
SLOPE |
6.000 |
|
|
|
|
mm7 |
<--- |
SLOPE |
7.000 |
|
|
|
|
mm8 |
<--- |
SLOPE |
8.000 |
|
|
|
|
mm6 |
<--- |
ICEPT |
1.000 |
|
|
|
|
mm7 |
<--- |
ICEPT |
1.000 |
|
|
|
|
mm8 |
<--- |
ICEPT |
1.000 |
|
|
|
|
|
|
|
Estimate |
ICEPT |
<--- |
grs23007 |
.003 |
SLOPE |
<--- |
grs23007 |
.003 |
ICEPT |
<--- |
eds23018 |
.492 |
ICEPT |
<--- |
ivs23483 |
.057 |
ICEPT |
<--- |
Bage |
-.326 |
ICEPT |
<--- |
ras23008 |
-.005 |
SLOPE |
<--- |
eds23018 |
-.034 |
SLOPE |
<--- |
ivs23483 |
.026 |
SLOPE |
<--- |
Bage |
-.475 |
SLOPE |
<--- |
ras23008 |
.038 |
MM0 |
<--- |
ICEPT |
.763 |
MM0 |
<--- |
SLOPE |
.000 |
MM1 |
<--- |
ICEPT |
.728 |
MM1 |
<--- |
SLOPE |
.113 |
MM2 |
<--- |
ICEPT |
.706 |
MM2 |
<--- |
SLOPE |
.218 |
MM3 |
<--- |
ICEPT |
.589 |
MM3 |
<--- |
SLOPE |
.273 |
MM4 |
<--- |
ICEPT |
.549 |
MM4 |
<--- |
SLOPE |
.339 |
MM5 |
<--- |
ICEPT |
.536 |
MM5 |
<--- |
SLOPE |
.414 |
mm6 |
<--- |
SLOPE |
.480 |
mm7 |
<--- |
SLOPE |
.548 |
mm8 |
<--- |
SLOPE |
.571 |
mm6 |
<--- |
ICEPT |
.517 |
mm7 |
<--- |
ICEPT |
.507 |
mm8 |
<--- |
ICEPT |
.462 |
|
|
|
Estimate |
S.E. |
C.R. |
P |
Label |
ICEPT |
|
|
24.428 |
.078 |
312.651 |
*** |
|
SLOPE |
|
|
-.693 |
.020 |
-34.377 |
*** |
|
|
|
|
Estimate |
S.E. |
C.R. |
P |
Label |
grs23007 |
<--> |
eds23018 |
-.059 |
.036 |
-1.666 |
.096 |
|
grs23007 |
<--> |
ivs23483 |
.005 |
.004 |
1.321 |
.187 |
|
grs23007 |
<--> |
Bage |
.013 |
.061 |
.210 |
.833 |
|
eds23018 |
<--> |
ivs23483 |
-.556 |
.031 |
-17.678 |
*** |
|
ras23008 |
<--> |
grs23007 |
.004 |
.005 |
.961 |
.336 |
|
ivs23483 |
<--> |
Bage |
.095 |
.051 |
1.870 |
.061 |
|
eds23018 |
<--> |
Bage |
-4.074 |
.488 |
-8.349 |
*** |
|
ras23008 |
<--> |
Bage |
-.411 |
.062 |
-6.661 |
*** |
|
ras23008 |
<--> |
eds23018 |
.431 |
.037 |
11.752 |
*** |
|
ras23008 |
<--> |
ivs23483 |
-.055 |
.004 |
-14.112 |
*** |
|
d1 |
<--> |
d2 |
.402 |
.107 |
3.777 |
*** |
|
|
|
|
Estimate |
grs23007 |
<--> |
eds23018 |
-.031 |
grs23007 |
<--> |
ivs23483 |
.024 |
grs23007 |
<--> |
Bage |
.004 |
eds23018 |
<--> |
ivs23483 |
-.347 |
ras23008 |
<--> |
grs23007 |
.018 |
ivs23483 |
<--> |
Bage |
.035 |
eds23018 |
<--> |
Bage |
-.157 |
ras23008 |
<--> |
Bage |
-.124 |
ras23008 |
<--> |
eds23018 |
.223 |
ras23008 |
<--> |
ivs23483 |
-.270 |
d1 |
<--> |
d2 |
.245 |
|
|
|
Estimate |
S.E. |
C.R. |
P |
Label |
grs23007 |
|
|
.244 |
.006 |
38.347 |
*** |
|
eds23018 |
|
|
15.111 |
.397 |
38.089 |
*** |
|
ivs23483 |
|
|
.170 |
.004 |
38.347 |
*** |
|
Bage |
|
|
44.765 |
1.167 |
38.347 |
*** |
|
ras23008 |
|
|
.246 |
.006 |
38.334 |
*** |
|
d1 |
|
|
9.509 |
.569 |
16.699 |
*** |
|
d2 |
|
|
.283 |
.032 |
8.828 |
*** |
|
E1 |
|
|
11.032 |
.552 |
19.999 |
*** |
|
E2 |
|
|
11.583 |
1.313 |
8.823 |
*** |
|
E3 |
|
|
10.667 |
.504 |
21.151 |
*** |
|
E4 |
|
|
20.717 |
2.549 |
8.129 |
*** |
|
E5 |
|
|
23.178 |
6.904 |
3.357 |
*** |
|
E6 |
|
|
20.686 |
.999 |
20.712 |
*** |
|
E7 |
|
|
19.035 |
1.929 |
9.867 |
*** |
|
E8 |
|
|
14.998 |
1.209 |
12.401 |
*** |
|
E9 |
|
|
20.032 |
2.892 |
6.928 |
*** |
|
Iteration |
|
Negative |
Condition # |
Smallest |
Diameter |
F |
NTries |
Ratio |
0 |
e |
3 |
|
-.116 |
9999.000 |
116727.749 |
0 |
9999.000 |
1 |
e* |
10 |
|
-.921 |
1.284 |
66658.862 |
14 |
.707 |
2 |
e |
11 |
|
-2.642 |
.305 |
63067.396 |
5 |
.777 |
3 |
e* |
3 |
|
-.198 |
.238 |
61370.672 |
5 |
.738 |
4 |
e |
3 |
|
-.090 |
.093 |
60493.438 |
5 |
.750 |
5 |
e |
2 |
|
-.014 |
.335 |
59416.523 |
8 |
.861 |
6 |
e |
0 |
1668579.660 |
|
.503 |
58253.263 |
5 |
.964 |
7 |
e |
0 |
29387.425 |
|
1.621 |
57918.551 |
4 |
.000 |
8 |
e |
0 |
4514.720 |
|
.338 |
57656.980 |
1 |
.988 |
9 |
e |
0 |
4651.941 |
|
.100 |
57558.468 |
1 |
1.211 |
10 |
e |
0 |
5484.413 |
|
.064 |
57531.628 |
1 |
1.256 |
11 |
e |
0 |
5569.580 |
|
.077 |
57520.279 |
1 |
1.288 |
12 |
e |
0 |
7109.571 |
|
.086 |
57515.408 |
1 |
1.259 |
13 |
e |
0 |
13943.510 |
|
.077 |
57513.933 |
1 |
1.201 |
14 |
e |
0 |
19875.663 |
|
.043 |
57513.716 |
1 |
1.110 |
15 |
e |
0 |
21556.448 |
|
.010 |
57513.708 |
1 |
1.026 |
16 |
e |
0 |
21700.112 |
|
.000 |
57513.708 |
1 |
1.001 |
The saturated model was not fitted to the data of at least one group.
For this reason, only the 'function of log likelihood', AIC and BCC are
reported. The likelihood ratio chi square statistic and other fit measures are
not reported.
Model |
NPAR |
CMIN |
Default model |
39 |
57513.708 |
Model |
AIC |
BCC |
BIC |
CAIC |
Default model |
57591.708 |
57592.108 |
|
|
Minimization: |
.156 |
Miscellaneous: |
.452 |
Bootstrap: |
.000 |
Total: |
.608 |