Report: Political Democracy
Model information
Model class:
ModelMeans
Number of samples:
75
Objective function:
FIML
Converged:
Yes
Description in semopy syntax:
# measurement model ind60 =~ x1 + x2 + x3 dem60 =~ y1 + y2 + y3 + y4 dem65 =~ y5 + y6 + y7 + y8 # regressions dem60 ~ ind60 dem65 ~ ind60 + dem60 # residual correlations y1 ~~ y5 y2 ~~ y4 + y6 y3 ~~ y7 y4 ~~ y8 y6 ~~ y8
all
dem65, ind60, y6, y1, dem60, x3, y3, y5, y2, x2, x1, y4, y7, y8
endogenous
y3, dem65, y5, y2, y6, y1, x2, x1, y4, y7, y8, dem60, x3
exogenous
ind60
observed
x1, x2, x3, y1, y2, y3, y4, y5, y6, y7, y8
latent
ind60, dem65, dem60
indicator
y3, y5, y2, y6, y1, x2, x1, y4, y7, y8, x3
output
observed_exogenous
1
_output
y3, y5, y2, y6, y1, x2, x1, y4, y7, y8, x3
inner
dem60, dem65, ind60
observed_exogenous_1
observed_exogenous_2
1
Estimates
Estimate
P-value
Measurement:
ind60 =~
x1
1.000
-
x2
2.180
0.000
x3
1.819
0.000
dem60 =~
y1
1.000
-
y2
1.257
0.000
y3
1.058
0.000
y4
1.265
0.000
dem65 =~
y5
1.000
-
y6
1.186
0.000
y7
1.280
0.000
y8
1.266
0.000
Regressions:
dem60 ~
ind60
1.483
0.000
dem65 ~
ind60
0.572
0.010
dem60
0.837
0.000
Intercepts:
x1
5.054
0.000
x2
4.792
0.000
x3
3.558
0.000
y1
5.465
0.000
y2
4.256
0.000
y3
6.563
0.000
y4
4.453
0.000
y5
5.136
0.000
y6
2.978
0.000
y7
6.196
0.000
y8
4.043
0.000
Variances:
dem65
0.172
0.422
dem60
3.956
0.000
ind60
0.448
0.000
y1
1.891
0.000
y2
7.373
0.000
y3
5.067
0.000
y4
3.148
0.000
y6
4.954
0.000
y5
2.351
0.000
x2
0.120
0.086
x1
0.082
0.000
y7
3.431
0.000
y8
3.254
0.000
x3
0.467
0.000
Covariances:
y1 ~
y5
0.624
0.082
y2 ~
y4
1.313
0.061
y6
2.153
0.003
y3 ~
y7
0.795
0.191
y4 ~
y8
0.348
0.431
y6 ~
y8
1.356
0.017
lval op rval Estimate Std. Err z-value p-value 0 dem60 ~ ind60 1.482999 0.399149 3.715401 0.000203 1 dem65 ~ ind60 0.572322 0.221313 2.586027 0.009709 2 dem65 ~ dem60 0.837346 0.098351 8.513859 0.0 3 x1 ~ ind60 1.000000 - - - 4 x2 ~ ind60 2.180375 0.13851 15.741609 0.0 5 x3 ~ ind60 1.818522 0.15196 11.967144 0.0 6 y1 ~ dem60 1.000000 - - - 7 y2 ~ dem60 1.256753 0.182439 6.888611 0.0 8 y3 ~ dem60 1.057746 0.151385 6.987136 0.0 9 y4 ~ dem60 1.264790 0.145006 8.722314 0.0 10 y5 ~ dem65 1.000000 - - - 11 y6 ~ dem65 1.185687 0.16881 7.023806 0.0 12 y7 ~ dem65 1.279531 0.159903 8.001935 0.0 13 y8 ~ dem65 1.265935 0.15811 8.00667 0.0 14 x1 ~ 1 5.054393 0.084062 60.126661 0.0 15 x2 ~ 1 4.792218 0.17327 27.657545 0.0 16 x3 ~ 1 3.557715 0.161233 22.065738 0.0 17 y1 ~ 1 5.464665 0.301854 18.10368 0.0 18 y2 ~ 1 4.256439 0.44987 9.461478 0.0 19 y3 ~ 1 6.563146 0.375891 17.460248 0.0 20 y4 ~ 1 4.452537 0.38391 11.597855 0.0 21 y5 ~ 1 5.136254 0.300511 17.091727 0.0 22 y6 ~ 1 2.978057 0.385931 7.716551 0.0 23 y7 ~ 1 6.196289 0.377202 16.426972 0.0 24 y8 ~ 1 4.043383 0.371319 10.889254 0.0 25 dem65 ~~ dem65 0.172487 0.214803 0.803001 0.421974 26 dem60 ~~ dem60 3.956039 0.921185 4.294508 0.000018 27 ind60 ~~ ind60 0.448436 0.086692 5.172765 0.0 28 y1 ~~ y5 0.623671 0.358319 1.740548 0.081763 29 y1 ~~ y1 1.891402 0.444423 4.255861 0.000021 30 y2 ~~ y4 1.313085 0.70198 1.870545 0.061408 31 y2 ~~ y6 2.152828 0.733771 2.933925 0.003347 32 y2 ~~ y2 7.372791 1.373882 5.366395 0.0 33 y3 ~~ y7 0.794961 0.607702 1.308143 0.190825 34 y3 ~~ y3 5.067487 0.951738 5.324453 0.0 35 y4 ~~ y8 0.348246 0.442238 0.787464 0.43101 36 y4 ~~ y4 3.147907 0.738783 4.260936 0.00002 37 y6 ~~ y8 1.356165 0.568281 2.386434 0.017013 38 y6 ~~ y6 4.953952 0.914241 5.418647 0.0 39 y5 ~~ y5 2.350969 0.480238 4.895427 0.000001 40 x2 ~~ x2 0.119802 0.069721 1.718314 0.085739 41 x1 ~~ x1 0.081551 0.01949 4.184259 0.000029 42 y7 ~~ y7 3.431334 0.712843 4.813589 0.000001 43 y8 ~~ y8 3.254068 0.694596 4.684837 0.000003 44 x3 ~~ x3 0.466708 0.090157 5.176583 0.0
Name of objective: FIML Optimization method: SLSQP Optimization successful. Optimization terminated successfully Objective value: 1579.333 Number of iterations: 68 Params: 2.180 1.819 1.257 1.058 1.265 1.186 1.280 1.266 5.054 4.792 3.558 5.465 4.256 6.563 4.453 5.136 2.978 6.196 4.043 1.483 0.572 0.837 0.624 1.891 1.313 2.153 7.373 0.795 5.067 0.348 3.148 1.356 4.954 0.172 2.351 0.120 0.082 3.431 3.254 3.956 0.467 0.448
Fit indices
| DoF | DoF Baseline | chi2 | chi2 p-value | chi2 Baseline |
|---|---|---|---|---|
| 24.000 | 44.000 | 21.058 | 0.635 | 30.291 |
| CFI | GFI | AGFI | NFI | TLI |
|---|---|---|---|---|
| 0.785 | 0.305 | -0.274 | 0.305 | 0.607 |
| RMSEA | AIC | BIC | LogLik |
|---|---|---|---|
| 0.000 | 82.983 | 180.318 | 0.508 |
Matrices
Covariance matrix
| x1 | x2 | x3 | y1 | y2 | y3 | y4 | y5 | y6 | y7 | y8 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| x1 | 0.53 | 0.98 | 0.81 | 0.72 | 0.61 | 0.78 | 1.14 | 1.07 | 0.84 | 0.92 | 1.09 |
| x2 | 0.98 | 2.25 | 1.78 | 1.26 | 1.47 | 1.53 | 2.21 | 2.04 | 1.78 | 1.97 | 2.20 |
| x3 | 0.81 | 1.78 | 1.95 | 0.90 | 1.15 | 1.03 | 1.81 | 1.56 | 1.55 | 1.60 | 1.67 |
| y1 | 0.72 | 1.26 | 0.90 | 6.79 | 6.17 | 5.76 | 6.01 | 5.00 | 5.67 | 5.73 | 5.60 |
| y2 | 0.61 | 1.47 | 1.15 | 6.17 | 15.37 | 5.76 | 9.38 | 5.53 | 9.26 | 7.43 | 7.65 |
| y3 | 0.78 | 1.53 | 1.03 | 5.76 | 5.76 | 10.62 | 6.60 | 4.87 | 4.66 | 6.91 | 5.56 |
| y4 | 1.14 | 2.21 | 1.81 | 6.01 | 9.38 | 6.60 | 11.07 | 5.63 | 7.34 | 7.39 | 7.91 |
| y5 | 1.07 | 2.04 | 1.56 | 5.00 | 5.53 | 4.87 | 5.63 | 6.73 | 4.91 | 5.74 | 5.27 |
| y6 | 0.84 | 1.78 | 1.55 | 5.67 | 9.26 | 4.66 | 7.34 | 4.91 | 11.22 | 6.66 | 8.14 |
| y7 | 0.92 | 1.97 | 1.60 | 5.73 | 7.43 | 6.91 | 7.39 | 5.74 | 6.66 | 10.66 | 7.49 |
| y8 | 1.09 | 2.20 | 1.67 | 5.60 | 7.65 | 5.56 | 7.91 | 5.27 | 8.14 | 7.49 | 10.39 |
| x1 | x2 | x3 | y1 | y2 | y3 | y4 | y5 | y6 | y7 | y8 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| x1 | 0.53 | 0.98 | 0.82 | 0.67 | 0.84 | 0.70 | 0.84 | 0.81 | 0.96 | 1.04 | 1.03 |
| x2 | 0.98 | 2.25 | 1.78 | 1.45 | 1.82 | 1.53 | 1.83 | 1.77 | 2.10 | 2.27 | 2.25 |
| x3 | 0.82 | 1.78 | 1.95 | 1.21 | 1.52 | 1.28 | 1.53 | 1.48 | 1.75 | 1.89 | 1.87 |
| y1 | 0.67 | 1.45 | 1.21 | 6.83 | 6.21 | 5.23 | 6.25 | 5.14 | 5.36 | 5.78 | 5.72 |
| y2 | 0.84 | 1.82 | 1.52 | 6.21 | 15.18 | 6.57 | 9.17 | 5.68 | 8.89 | 7.27 | 7.19 |
| y3 | 0.70 | 1.53 | 1.28 | 5.23 | 6.57 | 10.60 | 6.61 | 4.78 | 5.67 | 6.91 | 6.05 |
| y4 | 0.84 | 1.83 | 1.53 | 6.25 | 9.17 | 6.61 | 11.05 | 5.72 | 6.78 | 7.31 | 7.58 |
| y5 | 0.81 | 1.77 | 1.48 | 5.14 | 5.68 | 4.78 | 5.72 | 6.77 | 5.24 | 5.66 | 5.60 |
| y6 | 0.96 | 2.10 | 1.75 | 5.36 | 8.89 | 5.67 | 6.78 | 5.24 | 11.17 | 6.71 | 7.99 |
| y7 | 1.04 | 2.27 | 1.89 | 5.78 | 7.27 | 6.91 | 7.31 | 5.66 | 6.71 | 10.67 | 7.16 |
| y8 | 1.03 | 2.25 | 1.87 | 5.72 | 7.19 | 6.05 | 7.58 | 5.60 | 7.99 | 7.16 | 10.34 |
Model matrices
| dem60 | dem65 | ind60 | |
|---|---|---|---|
| dem60 | 0.00 | 0.00 | 1.48 |
| dem65 | 0.84 | 0.00 | 0.57 |
| ind60 | 0.00 | 0.00 | 0.00 |
| dem60 | dem65 | ind60 | |
|---|---|---|---|
| dem60 | 0.0 | 0.0 | 0.0 |
| dem65 | 0.0 | 0.0 | 0.0 |
| ind60 | 0.0 | 0.0 | 0.0 |
| dem60 | dem65 | ind60 | |
|---|---|---|---|
| dem60 | 0.0 | 0.0 | _b23 |
| dem65 | _b25 | 0.0 | _b24 |
| ind60 | 0.0 | 0.0 | 0.0 |
| 1 | |
|---|---|
| dem60 | 0.00 |
| dem65 | 0.00 |
| ind60 | 0.00 |
| 1 | |
|---|---|
| dem60 | 0.0 |
| dem65 | 0.0 |
| ind60 | 0.0 |
| 1 | |
|---|---|
| dem60 | 0.0 |
| dem65 | 0.0 |
| ind60 | 0.0 |
| 1 | |
|---|---|
| x1 | 5.05 |
| x2 | 4.79 |
| x3 | 3.56 |
| y1 | 5.46 |
| y2 | 4.26 |
| y3 | 6.56 |
| y4 | 4.45 |
| y5 | 5.14 |
| y6 | 2.98 |
| y7 | 6.20 |
| y8 | 4.04 |
| 1 | |
|---|---|
| x1 | 2.53 |
| x2 | 2.4 |
| x3 | 1.78 |
| y1 | 2.73 |
| y2 | 2.13 |
| y3 | 3.28 |
| y4 | 2.23 |
| y5 | 2.57 |
| y6 | 1.49 |
| y7 | 3.1 |
| y8 | 2.02 |
| 1 | |
|---|---|
| x1 | _b12 |
| x2 | _b13 |
| x3 | _b14 |
| y1 | _b15 |
| y2 | _b16 |
| y3 | _b17 |
| y4 | _b18 |
| y5 | _b19 |
| y6 | _b20 |
| y7 | _b21 |
| y8 | _b22 |
| dem60 | dem65 | ind60 | |
|---|---|---|---|
| x1 | 0.00 | 0.00 | 1.00 |
| x2 | 0.00 | 0.00 | 2.18 |
| x3 | 0.00 | 0.00 | 1.82 |
| y1 | 1.00 | 0.00 | 0.00 |
| y2 | 1.26 | 0.00 | 0.00 |
| y3 | 1.06 | 0.00 | 0.00 |
| y4 | 1.26 | 0.00 | 0.00 |
| y5 | 0.00 | 1.00 | 0.00 |
| y6 | 0.00 | 1.19 | 0.00 |
| y7 | 0.00 | 1.28 | 0.00 |
| y8 | 0.00 | 1.27 | 0.00 |
| dem60 | dem65 | ind60 | |
|---|---|---|---|
| x1 | 0.0 | 0.0 | 1.0 |
| x2 | 0.0 | 0.0 | 1.84 |
| x3 | 0.0 | 0.0 | 1.53 |
| y1 | 1.0 | 0.0 | 0.0 |
| y2 | 0.91 | 0.0 | 0.0 |
| y3 | 0.85 | 0.0 | 0.0 |
| y4 | 0.89 | 0.0 | 0.0 |
| y5 | 0.0 | 1.0 | 0.0 |
| y6 | 0.0 | 0.73 | 0.0 |
| y7 | 0.0 | 0.85 | 0.0 |
| y8 | 0.0 | 0.78 | 0.0 |
| dem60 | dem65 | ind60 | |
|---|---|---|---|
| x1 | 0.0 | 0.0 | _b1 |
| x2 | 0.0 | 0.0 | _b2 |
| x3 | 0.0 | 0.0 | _b3 |
| y1 | _b4 | 0.0 | 0.0 |
| y2 | _b5 | 0.0 | 0.0 |
| y3 | _b6 | 0.0 | 0.0 |
| y4 | _b7 | 0.0 | 0.0 |
| y5 | 0.0 | _b8 | 0.0 |
| y6 | 0.0 | _b9 | 0.0 |
| y7 | 0.0 | _b10 | 0.0 |
| y8 | 0.0 | _b11 | 0.0 |
| dem60 | dem65 | ind60 | |
|---|---|---|---|
| dem60 | 3.96 | 0.00 | 0.00 |
| dem65 | 0.00 | 0.17 | 0.00 |
| ind60 | 0.00 | 0.00 | 0.45 |
| dem60 | dem65 | ind60 | |
|---|---|---|---|
| dem60 | 0.05 | 0.0 | 0.0 |
| dem65 | 0.0 | 0.05 | 0.0 |
| ind60 | 0.0 | 0.0 | 0.05 |
| dem60 | dem65 | ind60 | |
|---|---|---|---|
| dem60 | _c18 | 0.0 | 0.0 |
| dem65 | 0.0 | _c12 | 0.0 |
| ind60 | 0.0 | 0.0 | _c20 |
| x1 | x2 | x3 | y1 | y2 | y3 | y4 | y5 | y6 | y7 | y8 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| x1 | 0.08 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| x2 | 0.00 | 0.12 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| x3 | 0.00 | 0.00 | 0.47 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| y1 | 0.00 | 0.00 | 0.00 | 1.89 | 0.00 | 0.00 | 0.00 | 0.62 | 0.00 | 0.00 | 0.00 |
| y2 | 0.00 | 0.00 | 0.00 | 0.00 | 7.37 | 0.00 | 1.31 | 0.00 | 2.15 | 0.00 | 0.00 |
| y3 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 5.07 | 0.00 | 0.00 | 0.00 | 0.79 | 0.00 |
| y4 | 0.00 | 0.00 | 0.00 | 0.00 | 1.31 | 0.00 | 3.15 | 0.00 | 0.00 | 0.00 | 0.35 |
| y5 | 0.00 | 0.00 | 0.00 | 0.62 | 0.00 | 0.00 | 0.00 | 2.35 | 0.00 | 0.00 | 0.00 |
| y6 | 0.00 | 0.00 | 0.00 | 0.00 | 2.15 | 0.00 | 0.00 | 0.00 | 4.95 | 0.00 | 1.36 |
| y7 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.79 | 0.00 | 0.00 | 0.00 | 3.43 | 0.00 |
| y8 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.35 | 0.00 | 1.36 | 0.00 | 3.25 |
| x1 | x2 | x3 | y1 | y2 | y3 | y4 | y5 | y6 | y7 | y8 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| x1 | 0.26 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| x2 | 0.0 | 1.13 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| x3 | 0.0 | 0.0 | 0.97 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| y1 | 0.0 | 0.0 | 0.0 | 3.39 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| y2 | 0.0 | 0.0 | 0.0 | 0.0 | 7.69 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| y3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5.31 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| y4 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5.53 | 0.0 | 0.0 | 0.0 | 0.0 |
| y5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.37 | 0.0 | 0.0 | 0.0 |
| y6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5.61 | 0.0 | 0.0 |
| y7 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5.33 | 0.0 |
| y8 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5.2 |
| x1 | x2 | x3 | y1 | y2 | y3 | y4 | y5 | y6 | y7 | y8 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| x1 | _c15 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| x2 | 0.0 | _c14 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| x3 | 0.0 | 0.0 | _c19 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| y1 | 0.0 | 0.0 | 0.0 | _c2 | 0.0 | 0.0 | 0.0 | _c1 | 0.0 | 0.0 | 0.0 |
| y2 | 0.0 | 0.0 | 0.0 | 0.0 | _c5 | 0.0 | _c3 | 0.0 | _c4 | 0.0 | 0.0 |
| y3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | _c7 | 0.0 | 0.0 | 0.0 | _c6 | 0.0 |
| y4 | 0.0 | 0.0 | 0.0 | 0.0 | _c3 | 0.0 | _c9 | 0.0 | 0.0 | 0.0 | _c8 |
| y5 | 0.0 | 0.0 | 0.0 | _c1 | 0.0 | 0.0 | 0.0 | _c13 | 0.0 | 0.0 | 0.0 |
| y6 | 0.0 | 0.0 | 0.0 | 0.0 | _c4 | 0.0 | 0.0 | 0.0 | _c11 | 0.0 | _c10 |
| y7 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | _c6 | 0.0 | 0.0 | 0.0 | _c16 | 0.0 |
| y8 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | _c8 | 0.0 | _c10 | 0.0 | _c17 |