Ordinales Modell

Modellübersicht

##  Family: cumulative 
##   Links: mu = probit; disc = log 
## Formula: stfdem ~ 1 + (1 | nuts2) 
##          disc ~ 1 + (1 | nuts2)
##    Data: cee12 (Number of observations: 7478) 
##   Draws: 3 chains, each with iter = 84000; warmup = 6000; thin = 6;
##          total post-warmup draws = 39000
## 
## Group-Level Effects: 
## ~nuts2 (Number of levels: 26) 
##                    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept)          0.59      0.19     0.30     1.04 1.00    21330    30182
## sd(disc_Intercept)     0.10      0.02     0.07     0.14 1.00    33258    37088
## 
## Population-Level Effects: 
##                Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept[1]      -3.95      1.11    -6.49    -2.13 1.00    19516    28174
## Intercept[2]      -3.11      0.88    -5.10    -1.67 1.00    19544    28063
## Intercept[3]      -2.18      0.62    -3.59    -1.17 1.00    19630    28381
## Intercept[4]      -1.25      0.37    -2.09    -0.65 1.00    19880    29343
## Intercept[5]      -0.43      0.17    -0.83    -0.16 1.00    21848    31180
## Intercept[6]       0.72      0.24     0.35     1.27 1.00    21078    30797
## Intercept[7]       1.63      0.48     0.87     2.72 1.00    19961    28988
## Intercept[8]       2.73      0.78     1.47     4.49 1.00    19750    27666
## Intercept[9]       3.98      1.12     2.15     6.54 1.00    19655    27521
## Intercept[10]      5.17      1.46     2.79     8.49 1.00    19610    28483
## disc_Intercept    -0.86      0.28    -1.39    -0.28 1.00    19553    27667
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).

Trace-Plots

Trace-Plot

Autokorrelation-Plots

Autokorrelation-Plot

Posterior-Verteilung

Posterior-Plot

Ordinales Nullmodell

Modellübersicht

##  Family: cumulative 
##   Links: mu = probit; disc = log 
## Formula: stfdem ~ 1 
##          disc ~ 1
##    Data: cee12 (Number of observations: 7478) 
##   Draws: 3 chains, each with iter = 84000; warmup = 6000; thin = 6;
##          total post-warmup draws = 39000
## 
## Population-Level Effects: 
##                Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept[1]      -3.69      1.07    -6.11    -1.95 1.00     9402    11043
## Intercept[2]      -2.90      0.84    -4.81    -1.53 1.00     9418    11059
## Intercept[3]      -2.04      0.59    -3.37    -1.08 1.00     9413    11098
## Intercept[4]      -1.18      0.34    -1.96    -0.62 1.00     9489    11165
## Intercept[5]      -0.42      0.13    -0.72    -0.22 1.00    10002    12414
## Intercept[6]       0.65      0.19     0.34     1.08 1.00     9636    11331
## Intercept[7]       1.49      0.43     0.79     2.47 1.00     9455    10896
## Intercept[8]       2.50      0.72     1.32     4.13 1.00     9436    10880
## Intercept[9]       3.63      1.05     1.92     6.00 1.00     9417    10846
## Intercept[10]      4.70      1.36     2.48     7.79 1.00     9405    10809
## disc_Intercept    -0.81      0.29    -1.35    -0.21 1.00     9401    10903
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).

Trace-Plots

Trace-Plot

Autokorrelation-Plots

Autokorrelation-Plot

Posterior-Verteilung

Posterior-Plot

Metrisches Modell

Modellübersicht

##  Family: student 
##   Links: mu = identity; sigma = log; nu = identity 
## Formula: stfdem ~ 1 + (1 | nuts2) 
##          sigma ~ 1 + (1 | nuts2)
##    Data: cee12 (Number of observations: 7478) 
##   Draws: 3 chains, each with iter = 66000; warmup = 6000; thin = 6;
##          total post-warmup draws = 30000
## 
## Group-Level Effects: 
## ~nuts2 (Number of levels: 26) 
##                     Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept)           0.58      0.10     0.43     0.80 1.00    22750    27207
## sd(sigma_Intercept)     0.08      0.02     0.05     0.11 1.00    26111    27440
## 
## Population-Level Effects: 
##                 Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept           4.76      0.12     4.52     4.99 1.00    16492    22911
## sigma_Intercept     0.87      0.02     0.83     0.90 1.00    26961    27865
## 
## Family Specific Parameters: 
##    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## nu   192.14     56.02   105.22   321.09 1.00    28461    28488
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).

Trace-Plots

Trace-Plot

Autokorrelation-Plots

Autokorrelation-Plot

Posterior-Verteilung

Posterior-Plot

Metrisches Nullmodell

Modellübersicht

##  Family: student 
##   Links: mu = identity; sigma = log; nu = identity 
## Formula: stfdem ~ 1 
##          sigma ~ 1
##    Data: cee12 (Number of observations: 7478) 
##   Draws: 3 chains, each with iter = 11500; warmup = 1500; thin = 1;
##          total post-warmup draws = 30000
## 
## Population-Level Effects: 
##                 Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept           4.79      0.03     4.73     4.85 1.00    21730    17668
## sigma_Intercept     0.90      0.01     0.88     0.91 1.00    22446    18521
## 
## Family Specific Parameters: 
##    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## nu   205.41     57.21   115.30   337.24 1.00    21044    18452
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).

Trace-Plots

Trace-Plot

Autokorrelation-Plots

Autokorrelation-Plot

Posterior-Verteilung

Posterior-Plot

Copyright:
Benedikt Philipp Kleer, 2022 (Online-Appendix zur Promotion, eingereicht am 14. September 2022, Fachbereich 03, Justus-Liebig-Universität Gießen).