Ordinales Modell

Modellübersicht

##  Family: cumulative 
##   Links: mu = probit; disc = log 
## Formula: outcome ~ 1 + (1 | nuts2) 
##          disc ~ 1 + (1 | nuts2)
##    Data: cee12 (Number of observations: 7151) 
##   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)          0.67      0.22     0.34     1.18 1.00    21005    29292
## sd(disc_Intercept)     0.06      0.02     0.03     0.09 1.00    35576    37079
## 
## Population-Level Effects: 
##                Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept[1]      -3.95      1.12    -6.47    -2.12 1.00    19820    28342
## Intercept[2]      -2.86      0.81    -4.70    -1.53 1.00    19753    28206
## Intercept[3]      -1.88      0.55    -3.12    -0.99 1.00    19754    28052
## Intercept[4]      -0.93      0.30    -1.62    -0.46 1.00    20011    28505
## Intercept[5]       0.03      0.14    -0.25     0.32 1.00    20057    29485
## Intercept[6]       1.01      0.32     0.51     1.74 1.00    20262    29485
## Intercept[7]       2.05      0.59     1.09     3.40 1.00    20002    28667
## Intercept[8]       3.04      0.86     1.64     5.00 1.00    19926    28242
## Intercept[9]       4.17      1.17     2.25     6.84 1.00    19894    28363
## Intercept[10]      5.52      1.55     2.98     9.05 1.00    19811    28736
## disc_Intercept    -0.58      0.28    -1.11    -0.01 1.00    19652    28218
## 
## 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: outcome ~ 1 
##          disc ~ 1
##    Data: cee12 (Number of observations: 7151) 
##   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]      -3.70      1.06    -6.12    -1.95 1.00    12136    13611
## Intercept[2]      -2.65      0.76    -4.40    -1.40 1.00    12173    13574
## Intercept[3]      -1.73      0.50    -2.85    -0.91 1.00    12181    13599
## Intercept[4]      -0.83      0.24    -1.38    -0.44 1.00    12247    13879
## Intercept[5]       0.06      0.03     0.01     0.14 1.00    25045    27085
## Intercept[6]       0.98      0.28     0.51     1.62 1.00    12232    13787
## Intercept[7]       1.93      0.56     1.02     3.19 1.00    12199    13701
## Intercept[8]       2.83      0.82     1.49     4.69 1.00    12149    13734
## Intercept[9]       3.83      1.10     2.01     6.33 1.00    12164    13618
## Intercept[10]      5.04      1.45     2.65     8.35 1.00    12095    13678
## disc_Intercept    -0.56      0.29    -1.10     0.04 1.00    12154    13567
## 
## 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: outcome ~ 1 + (1 | nuts2) 
##          sigma ~ 1 + (1 | nuts2)
##    Data: cee12 (Number of observations: 7151) 
##   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)           0.67      0.11     0.50     0.91 1.00    22505    27303
## sd(sigma_Intercept)     0.05      0.02     0.02     0.08 1.00    25391    24230
## 
## Population-Level Effects: 
##                 Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept           4.43      0.14     4.17     4.70 1.00    14660    22051
## sigma_Intercept     0.62      0.01     0.60     0.65 1.00    28703    29717
## 
## Family Specific Parameters: 
##    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## nu   136.29     47.51    66.60   249.90 1.00    29861    29335
## 
## 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: outcome ~ 1 
##          sigma ~ 1
##    Data: cee12 (Number of observations: 7151) 
##   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           4.42      0.02     4.37     4.46 1.00    21449    18643
## sigma_Intercept     0.67      0.01     0.65     0.69 1.00    20631    19346
## 
## Family Specific Parameters: 
##    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## nu   157.87     50.30    81.16   276.16 1.00    20820    19834
## 
## 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).