## 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

DoFDoF Baselinechi2chi2 p-valuechi2 Baseline
24.00044.00021.0580.63530.291
CFIGFIAGFINFITLI
0.7850.305-0.2740.3050.607
RMSEAAICBICLogLik
0.00082.983180.3180.508

### 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