R Under development (unstable) (2025-01-06 r87534 ucrt) -- "Unsuffered Consequences"
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> # set.seed(123)
> # 
> # ## for Q-matrix validation procedures
> # library(Qval)
> # 
> # ## for the dataset PISA2000
> # library(CDM)
> # 
> # # ########################### PISA 2000 ##################################
> # Q <- as.matrix(data.pisa00R.ct$q.matrix)[, -c(7, 8)]
> # Y <- as.matrix(data.pisa00R.ct$data[, 5:30])
> # Y[, c(7, 12, 13)][which(Y[, c(7, 12, 13)] < 2)] <- 0
> # Y[, c(7, 12, 13)][which(Y[, c(7, 12, 13)] > 1)] <- 1
> # 
> # print(Q)
> # 
> # ######## GDI ########
> # Qval.obj <- validation(Y, Q, model="GDINA",
> #                        method="GDI", search.method="PAA",
> #                        iter.level = "test", maxitr=1, verbose=1)
> # print(Qval.obj$Q.sug)
> # 
> # ######## Hull ########
> # Qval.obj <- validation(Y, Q, model="GDINA",
> #                        method="Hull", search.method="ESA",
> #                        iter.level = "item", maxitr=150, verbose=1)
> # 
> # head(Qval.obj$Q.sug)
> # 
> # plot(Qval.obj$Hull.fit, i=2)
> # 
> # ######## Wald ########
> # Qval.obj <- validation(Y, Q, model="GDINA",
> #                        method="Wald", alpha.level=0.05, search.method="stepwise",
> #                        iter.level = "test", maxitr=1, verbose=1)
> # 
> # head(Qval.obj$Q.sug)
> # 
> # CDM.obj <- CDM(Y, Q)
> # 
> # q1 <- c(1, 0, 0, 1, 0, 0)
> # q2 <- c(0, 0, 0, 1, 0, 0)
> # Wald.test(CDM.obj, q1, q2, i=1)
> # 
> # ######## fit ########
> # Qval.obj <- validation(Y, Q, model="GDINA",
> #                        method="MLR-B", search.method="PAA",
> #                        iter.level = "test", maxitr=1, verbose=1)
> # 
> # fit(Y, Q, model="GDINA")
> # 
> # ######## beta ########
> # Qval.obj <- validation(Y, Q, model="GDINA",
> #                        method="beta", search.method="PAA",
> #                        criter="AIC",
> #                        iter.level = "test", maxitr=1, verbose=1)
> # 
> # head(Qval.obj$Q.sug)
> 
> proc.time()
   user  system elapsed 
   0.14    0.03    0.15