Summarizing Hidden Markov Cognitive Diagnosis Model Fits

Source: R/summary.R

summary method for class "hmcdm" or "summary.hmcdm".

# S3 method for summary.hmcdm
print(x, ...)

# S3 method for hmcdm
summary(object, ...)

Arguments

x

an object of class "hmcdm.summary".

...

further arguments passed to or from other methods.

object

a fitted model object of class "hmcdm".

Value

The function summary.hmcdm computes and returns a list of point estimates of model parameters and model fit measures including DIC and PPP-values.

See also

hmcdm()

Examples

# \donttest{
output_FOHM = hmcdm(Y_real_array,Q_matrix,"DINA_FOHM",Design_array,1000,500)
#> 0
summary(output_FOHM)
#> 
#> Model: DINA_FOHM 
#> 
#> Item Parameters:
#>   ss_EAP gs_EAP
#>  0.03414 0.6741
#>  0.04321 0.6602
#>  0.14872 0.5481
#>  0.07637 0.5344
#>  0.18316 0.4348
#>    ... 45 more items
#> 
#> Transition Parameters:
#>  [1] 0.727967 0.013353 0.030778 0.009709 0.015024 0.024111 0.022824 0.013613
#>  [9] 0.037839 0.010692 0.028328 0.011130 0.013181 0.011106 0.016441 0.013904
#>    ... 15 more rows
#> 
#> Class Probabilities:
#>       pis_EAP
#> 0000 0.101867
#> 0001 0.006419
#> 0010 0.012820
#> 0011 0.011264
#> 0100 0.071377
#>    ... 11 more classes
#> 
#> Deviance Information Criterion (DIC): 17953.18 
#> 
#> Posterior Predictive P-value (PPP):
#> M1: 0.556
#> M2:  0.49
#> total scores:  0.6339
# }