LEM: log-linear and event history analysis with missing data.
Developed by Jeroen Vermunt (c), Tilburg University, The Netherlands.
Version 1.0 (September 18, 1997).
*** INPUT ***
man 3
dim 2 6 6
lab C W H
***HOMOGAMY (MAT1) with changing RCII
mod {cov(H,1) cov(H,1) cov(H,1) cov(H,1) cov(H,1)}
des[
1 0 0 0 0 -1
0 1 0 0 0 -1
0 0 1 0 0 -1
0 0 0 1 0 -1
0 0 0 0 1 -1
]
dat sample.fre
nco
*** STATISTICS ***
Number of iterations = 25
Converge criterion = 0.0000006002
X-squared = 14181.7959 (0.0000)
L-squared = 11171.3442 (0.0000)
Cressie-Read = 12616.3463 (0.0000)
Dissimilarity index = 0.4448
Degrees of freedom = 66
Log-likelihood = -36482.70566
Number of parameters = 5 (+1)
Sample size = 9684.0
BIC(L-squared) = 10565.5810
AIC(L-squared) = 11039.3442
BIC(log-likelihood) = 73011.3025
AIC(log-likelihood) = 72975.4113
Eigenvalues information matrix
3317.3117 1775.1841 1292.5114 852.5569 317.1529
*** LOG-LINEAR PARAMETERS ***
* TABLE CWH [or P(CWH)] *
effect beta std err z-value exp(beta) Wald df prob
main 4.3243 75.5102
cov(H)
1 0.0378 0.0317 1.191 1.0385 1.42 1 0.234
cov(H)
1 1.7772 0.0206 86.426 5.9131 7469.54 1 0.000
cov(H)
1 0.8285 0.0249 33.285 2.2900 1107.88 1 0.000
cov(H)
1 -0.1333 0.0337 -3.951 0.8752 15.61 1 0.000
cov(H)
1 -1.2144 0.0527 -23.048 0.2969 531.23 1 0.000
~~~~~~~~~~~~~~~~~~~~~~~~~~~~
LEM: log-linear and event history analysis with missing data.
Developed by Jeroen Vermunt (c), Tilburg University, The Netherlands.
Version 1.0 (September 18, 1997).
*** INPUT ***
man 3
dim 2 6 6
lab C W H
***HOMOGAMY (MAT1) with changing RCII
mod {H}
dat sample.fre
nco
*** STATISTICS ***
Number of iterations = 2
Converge criterion = 0.0000000000
X-squared = 14181.8075 (0.0000)
L-squared = 11171.3442 (0.0000)
Cressie-Read = 12616.3527 (0.0000)
Dissimilarity index = 0.4448
Degrees of freedom = 66
Log-likelihood = -36482.70566
Number of parameters = 5 (+1)
Sample size = 9684.0
BIC(L-squared) = 10565.5810
AIC(L-squared) = 11039.3442
BIC(log-likelihood) = 73011.3025
AIC(log-likelihood) = 72975.4113
Eigenvalues information matrix
3317.3172 1775.1003 1292.5355 852.5780 317.1440
*** LOG-LINEAR PARAMETERS ***
* TABLE CWH [or P(CWH)] *
effect beta std err z-value exp(beta) Wald df prob
main 4.3243 75.5092
H
1 0.0378 0.0317 1.191 1.0385
2 1.7772 0.0206 86.426 5.9132
3 0.8286 0.0249 33.285 2.2900
4 -0.1333 0.0337 -3.951 0.8752
5 -1.2145 0.0527 -23.049 0.2969
6 -1.2957 0.2737 7740.30 5 0.000
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