
Call:
clm_imp(formula = O1 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3 
     0      0      0 

Call:
clm_imp(formula = O2 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O2" 


Coefficients:
O2 > 1 O2 > 2 O2 > 3 
     0      0      0 

Call:
clm_imp(formula = O1 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3     C1 
     0      0      0      0 

Call:
clm_imp(formula = O2 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O2" 


Coefficients:
O2 > 1 O2 > 2 O2 > 3     C1 
     0      0      0      0 

Call:
clm_imp(formula = O1 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3     C2 
     0      0      0      0 

Call:
clm_imp(formula = O2 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O2" 


Coefficients:
O2 > 1 O2 > 2 O2 > 3     C2 
     0      0      0      0 

Call:
lm_imp(formula = C1 ~ O1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian linear model for "C1" 


Coefficients:
(Intercept)        O1.L        O1.Q        O1.C 
          0           0           0           0 


Residual standard deviation:
sigma_C1 
       0 

Call:
lm_imp(formula = C1 ~ O2, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian linear model for "C1" 


Coefficients:
(Intercept)         O22         O23         O24 
          0           0           0           0 


Residual standard deviation:
sigma_C1 
       0 

Call:
clm_imp(formula = O1 ~ M2 + O2 * abs(C1 - C2) + log(C1), data = wideDF, 
    n.adapt = 5, n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
          O1 > 1           O1 > 2           O1 > 3              M22 
               0                0                0                0 
             M23              M24              O22              O23 
               0                0                0                0 
             O24     abs(C1 - C2)          log(C1) O22:abs(C1 - C2) 
               0                0                0                0 
O23:abs(C1 - C2) O24:abs(C1 - C2) 
               0                0 

Call:
clm_imp(formula = O1 ~ ifelse(as.numeric(O2) > as.numeric(M1), 
    1, 0) * abs(C1 - C2) + log(C1), data = wideDF, n.adapt = 5, 
    n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
                                                    O1 > 1 
                                                         0 
                                                    O1 > 2 
                                                         0 
                                                    O1 > 3 
                                                         0 
             ifelse(as.numeric(O2) > as.numeric(M1), 1, 0) 
                                                         0 
                                              abs(C1 - C2) 
                                                         0 
                                                   log(C1) 
                                                         0 
ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2) 
                                                         0 

Call:
clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24     C1     C2 
     0      0      0      0      0      0      0      0      0      0      0 
    C1     C2     C1     C2 
     0      0      0      0 

Call:
clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24  C1:C2     C1 
     0      0      0      0      0      0      0      0      0      0      0 
    C2     C1     C2     C1     C2 
     0      0      0      0      0 

Call:
clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
        C2), seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24     C1     C2 
     0      0      0      0      0      0      0      0      0      0      0 
 C1:C2     C1     C2  C1:C2     C1     C2  C1:C2 
     0      0      0      0      0      0      0 

Call:
clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 
     0      0      0      0      0      0      0      0      0      0      0 
M24:C2     C1     C2     C1     C2     C1     C2 
     0      0      0      0      0      0      0 

Call:
clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
        M2 * C2 + O2, seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2 
     0      0      0 

Call:
clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3    M22    M23    M24    O22    O23    O24     C1     C2 
     0      0      0      0      0      0      0      0      0      0      0 
    C1     C2     C1     C2 
     0      0      0      0 

Call:
clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3    M22    M23    M24    O22    O23    O24  C1:C2     C1 
     0      0      0      0      0      0      0      0      0      0      0 
    C2     C1     C2     C1     C2 
     0      0      0      0      0 

Call:
clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
        C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3    M22    M23    M24    O22    O23    O24     C1     C2 
     0      0      0      0      0      0      0      0      0      0      0 
 C1:C2     C1     C2  C1:C2     C1     C2  C1:C2 
     0      0      0      0      0      0      0 

Call:
clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3    M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 
     0      0      0      0      0      0      0      0      0      0      0 
M24:C2     C1     C2     C1     C2     C1     C2 
     0      0      0      0      0      0      0 

Call:
clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
        M2 * C2 + O2, rev = "O1", seed = 2020, warn = FALSE, 
    mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2 
     0      0      0 
$m0a

Call:
clm_imp(formula = O1 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3 
     0      0      0 

$m0b

Call:
clm_imp(formula = O2 ~ 1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O2" 


Coefficients:
O2 > 1 O2 > 2 O2 > 3 
     0      0      0 

$m1a

Call:
clm_imp(formula = O1 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3     C1 
     0      0      0      0 

$m1b

Call:
clm_imp(formula = O2 ~ C1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O2" 


Coefficients:
O2 > 1 O2 > 2 O2 > 3     C1 
     0      0      0      0 

$m2a

Call:
clm_imp(formula = O1 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3     C2 
     0      0      0      0 

$m2b

Call:
clm_imp(formula = O2 ~ C2, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O2" 


Coefficients:
O2 > 1 O2 > 2 O2 > 3     C2 
     0      0      0      0 

$m3a

Call:
lm_imp(formula = C1 ~ O1, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian linear model for "C1" 


Coefficients:
(Intercept)        O1.L        O1.Q        O1.C 
          0           0           0           0 


Residual standard deviation:
sigma_C1 
       0 

$m3b

Call:
lm_imp(formula = C1 ~ O2, data = wideDF, n.adapt = 5, n.iter = 10, 
    seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian linear model for "C1" 


Coefficients:
(Intercept)         O22         O23         O24 
          0           0           0           0 


Residual standard deviation:
sigma_C1 
       0 

$m4a

Call:
clm_imp(formula = O1 ~ M2 + O2 * abs(C1 - C2) + log(C1), data = wideDF, 
    n.adapt = 5, n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
          O1 > 1           O1 > 2           O1 > 3              M22 
               0                0                0                0 
             M23              M24              O22              O23 
               0                0                0                0 
             O24     abs(C1 - C2)          log(C1) O22:abs(C1 - C2) 
               0                0                0                0 
O23:abs(C1 - C2) O24:abs(C1 - C2) 
               0                0 

$m4b

Call:
clm_imp(formula = O1 ~ ifelse(as.numeric(O2) > as.numeric(M1), 
    1, 0) * abs(C1 - C2) + log(C1), data = wideDF, n.adapt = 5, 
    n.iter = 10, seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
                                                    O1 > 1 
                                                         0 
                                                    O1 > 2 
                                                         0 
                                                    O1 > 3 
                                                         0 
             ifelse(as.numeric(O2) > as.numeric(M1), 1, 0) 
                                                         0 
                                              abs(C1 - C2) 
                                                         0 
                                                   log(C1) 
                                                         0 
ifelse(as.numeric(O2) > as.numeric(M1), 1, 0):abs(C1 - C2) 
                                                         0 

$m5a

Call:
clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24     C1     C2 
     0      0      0      0      0      0      0      0      0      0      0 
    C1     C2     C1     C2 
     0      0      0      0 

$m5b

Call:
clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24  C1:C2     C1 
     0      0      0      0      0      0      0      0      0      0      0 
    C2     C1     C2     C1     C2 
     0      0      0      0      0 

$m5c

Call:
clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
        C2), seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24     C1     C2 
     0      0      0      0      0      0      0      0      0      0      0 
 C1:C2     C1     C2  C1:C2     C1     C2  C1:C2 
     0      0      0      0      0      0      0 

$m5d

Call:
clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3    M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 
     0      0      0      0      0      0      0      0      0      0      0 
M24:C2     C1     C2     C1     C2     C1     C2 
     0      0      0      0      0      0      0 

$m5e

Call:
clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
        M2 * C2 + O2, seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 > 1 O1 > 2 O1 > 3     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2 
     0      0      0 

$m6a

Call:
clm_imp(formula = O1 ~ C1 + C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3    M22    M23    M24    O22    O23    O24     C1     C2 
     0      0      0      0      0      0      0      0      0      0      0 
    C1     C2     C1     C2 
     0      0      0      0 

$m6b

Call:
clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3    M22    M23    M24    O22    O23    O24  C1:C2     C1 
     0      0      0      0      0      0      0      0      0      0      0 
    C2     C1     C2     C1     C2 
     0      0      0      0      0 

$m6c

Call:
clm_imp(formula = O1 ~ C1 * C2 + M2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 * 
        C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3    M22    M23    M24    O22    O23    O24     C1     C2 
     0      0      0      0      0      0      0      0      0      0      0 
 C1:C2     C1     C2  C1:C2     C1     C2  C1:C2 
     0      0      0      0      0      0      0 

$m6d

Call:
clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = list(O1 = ~C1 + 
        C2), rev = "O1", seed = 2020, warn = FALSE, mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3    M22    M23    M24    O22    O23    O24 M22:C2 M23:C2 
     0      0      0      0      0      0      0      0      0      0      0 
M24:C2     C1     C2     C1     C2     C1     C2 
     0      0      0      0      0      0      0 

$m6e

Call:
clm_imp(formula = O1 ~ C1 + M2 * C2 + O2, data = wideDF, n.adapt = 5, 
    n.iter = 10, monitor_params = list(other = "p_O1"), nonprop = ~C1 + 
        M2 * C2 + O2, rev = "O1", seed = 2020, warn = FALSE, 
    mess = FALSE)

 Bayesian cumulative logit model for "O1" 


Coefficients:
O1 = 1 O1 = 2 O1 = 3     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2     C1    M22    M23    M24     C2    O22    O23    O24 
     0      0      0      0      0      0      0      0      0      0      0 
M22:C2 M23:C2 M24:C2 
     0      0      0 

