summary.validation.RdSummary method for validation objects
# S3 method for class 'validation'
summary(object, ...)An object of class "validation" returned by the validation function.
Additional arguments.
A list containing summary statistics of the validated Q-matrix.
set.seed(123)
library(Qval)
K <- 3
I <- 20
Q <- sim.Q(K, I)
IQ <- list(
P0 = runif(I, 0.0, 0.2),
P1 = runif(I, 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
MQ <- sim.MQ(Q, 0.1)
#> rate of mis-specifications = 0.1
#> rate of over-specifications = 0.07
#> rate of under-specifications = 0.03
CDM.obj <- CDM(data.obj$dat, MQ)
#>
Iter = 1 Max. abs. change = 0.55372 Deviance = 11376.15
Iter = 2 Max. abs. change = 0.20531 Deviance = 8796.31
Iter = 3 Max. abs. change = 0.09493 Deviance = 8725.28
Iter = 4 Max. abs. change = 0.02365 Deviance = 8719.03
Iter = 5 Max. abs. change = 0.01674 Deviance = 8718.11
Iter = 6 Max. abs. change = 0.01408 Deviance = 8717.82
Iter = 7 Max. abs. change = 0.01043 Deviance = 8717.68
Iter = 8 Max. abs. change = 0.00706 Deviance = 8717.62
Iter = 9 Max. abs. change = 0.00454 Deviance = 8717.58
Iter = 10 Max. abs. change = 0.00201 Deviance = 8717.57
Iter = 11 Max. abs. change = 0.00717 Deviance = 8717.56
Iter = 12 Max. abs. change = 0.00277 Deviance = 8717.56
Iter = 13 Max. abs. change = 0.00088 Deviance = 8717.56
Iter = 14 Max. abs. change = 0.00025 Deviance = 8717.55
Iter = 15 Max. abs. change = 0.00016 Deviance = 8717.55
Iter = 16 Max. abs. change = 0.00035 Deviance = 8717.55
Iter = 17 Max. abs. change = 0.00021 Deviance = 8717.55
Iter = 18 Max. abs. change = 0.00318 Deviance = 8717.55
Iter = 19 Max. abs. change = 0.00007 Deviance = 8717.55
Q.GDI.obj <- validation(data.obj$dat, MQ, CDM.obj, method = "GDI")
#> GDI method with PAA in test level iteration ...
#> Iter = 1/ 1, 9 items have changed, ΔPVAF=1.04934
summary(Q.GDI.obj)
#> Call:
#> validation(Y = data.obj$dat, Q = MQ,
#> CDM.obj = CDM.obj, method = "GDI")
#>
#> ==============================================
#>
#> Suggested Q-matrix:
#>
#> A1 A2 A3
#> item 1 0 1 0
#> item 2 1 0 1
#> item 3 1 0* 1
#> item 4 0 0 1
#> item 5 1* 0 1
#> item 6 0* 0 1
#> item 7 0 0 1
#> item 8 0* 1 0
#> item 9 0 0 1
#> item 10 0* 1 1
#> item 11 1 1 0*
#> item 12 0 1 1*
#> item 13 1 0 0
#> item 14 0 0 1
#> item 15 1 0* 0
#> item 16 0 1 1
#> item 17 1 1 1
#> item 18 1 0 1
#> item 19 0 1 0*
#> item 20 1 1 1
#> Note: * denotes a modified element.