Plot Method for CDM Objects

This function generates a bar plot visualizing the distribution of \(\boldsymbol{\alpha}\). The plot includes both the frequency and proportion (percentage) of each pattern. Frequencies are displayed as bars, and proportions are annotated both above the bars and as a secondary axis on the right.

# S3 method for class 'CDM'
plot(x, ...)

Arguments

x

An object of class CDM, typically returned by CDM function.

...

Additional arguments (currently unused).

Value

None. This function is used for side effects (plotting).

Examples

set.seed(123)
library(Qval)

Q <- sim.Q(3, 20)
IQ <- list(
  P0 = runif(20, 0.0, 0.2),
  P1 = runif(20, 0.8, 1.0)
)
data.obj <- sim.data(Q = Q, N = 500, IQ = IQ,
                     model = "GDINA", distribute = "horder")
#> distribute =  horder 
#>  model =  GDINA 
#>  number of attributes:  3 
#>  number of items:  20 
#>  num of examinees:  500 
#>  average of P0 =  0.083 
#>  average of P1 =  0.894 
#> theta_mean =  -0.055 , theta_sd = 0.996 
#>  a =  1.5 1.5 1.5 
#>  b =  -1.5 1.5 0 
CDM.obj <- CDM(data.obj$dat, Q, model = "GDINA", 
               method = "EM", maxitr = 2000, verbose = 1)
#> 
Iter = 1  Max. abs. change = 0.57951  Deviance  = 10238.69                                                                                  
Iter = 2  Max. abs. change = 0.09509  Deviance  = 8501.84                                                                                  
Iter = 3  Max. abs. change = 0.03995  Deviance  = 8478.24                                                                                  
Iter = 4  Max. abs. change = 0.01792  Deviance  = 8477.13                                                                                  
Iter = 5  Max. abs. change = 0.02604  Deviance  = 8477.02                                                                                  
Iter = 6  Max. abs. change = 0.01142  Deviance  = 8476.97                                                                                  
Iter = 7  Max. abs. change = 0.01740  Deviance  = 8476.96                                                                                  
Iter = 8  Max. abs. change = 0.00686  Deviance  = 8476.95                                                                                  
Iter = 9  Max. abs. change = 0.00466  Deviance  = 8476.94                                                                                  
Iter = 10  Max. abs. change = 0.00253  Deviance  = 8476.94                                                                                  
Iter = 11  Max. abs. change = 0.00030  Deviance  = 8476.94                                                                                  
Iter = 12  Max. abs. change = 0.00014  Deviance  = 8476.94                                                                                  
Iter = 13  Max. abs. change = 0.00016  Deviance  = 8476.94                                                                                  
Iter = 14  Max. abs. change = 0.00760  Deviance  = 8476.94                                                                                  
Iter = 15  Max. abs. change = 0.00246  Deviance  = 8476.94                                                                                  
Iter = 16  Max. abs. change = 0.00502  Deviance  = 8476.94                                                                                  
Iter = 17  Max. abs. change = 0.00017  Deviance  = 8476.94                                                                                  
Iter = 18  Max. abs. change = 0.00109  Deviance  = 8476.94                                                                                  
Iter = 19  Max. abs. change = 0.00004  Deviance  = 8476.94                                                                                  
plot(CDM.obj)