if (FALSE) {
#example test
set.seed(1234)
nitems <- 25
itemnames <- paste0('Item.', 1:nitems)
a <- matrix(rlnorm(nitems, .2, .3))
d <- matrix(rnorm(nitems))
dat <- simdata(a, d, 500, itemtype = 'dich')
colnames(dat) <- itemnames
mod <- mirt(dat, 1, verbose = FALSE, TOL = .01)
# simple math items
questions <- answers <- character(nitems)
choices <- matrix(NA, nitems, 5)
spacing <- floor(d - min(d)) + 1 #easier items have more variation in the options
for(i in 1:nitems){
n1 <- sample(1:50, 1)
n2 <- sample(51:100, 1)
ans <- n1 + n2
questions[i] <- paste0(n1, ' + ', n2, ' = ?')
answers[i] <- as.character(ans)
ch <- ans + sample(c(-5:-1, 1:5) * spacing[i,], 5)
ch[sample(1:5, 1)] <- ans
choices[i, ] <- as.character(ch)
}
df <- data.frame(Question=questions, Option=choices,
Type = 'radio', stringsAsFactors = FALSE)
df$Answer <- answers
pat <- generate_pattern(mod, Theta = 0, df)
#------------------------------------------------
# administer items in sequence
customNextItem <- function(person, design, test){
# browser()
items_left_2_choose_from <- extract.mirtCAT(person, 'items_in_bank')
min(items_left_2_choose_from)
}
res <- mirtCAT(df, local_pattern=pat,
design = list(customNextItem=customNextItem))
summary(res)
#------------------------------------------------
# administer items in order, but stop after 10 items
customNextItem <- function(person, design, test){
items_left_2_choose_from <- extract.mirtCAT(person, 'items_in_bank')
items_answered <- extract.mirtCAT(person, 'items_answered')
total <- sum(!is.na(items_answered))
ret <- if(total < 10) min(items_left_2_choose_from)
else return(NA)
ret
}
res <- mirtCAT(df, local_pattern=pat,
design = list(customNextItem=customNextItem))
summary(res)
#------------------------------------------------
# using findNextItem() and stopping after 10 items
customNextItem <- function(person, design, test){
items_answered <- extract.mirtCAT(person, 'items_answered')
total <- sum(!is.na(items_answered))
ret <- NA
if(total < 10)
ret <- findNextItem(person=person, test=test, design=design, criteria = 'MI')
ret
}
res <- mirtCAT(df, mod, local_pattern=pat, start_item = 'MI',
design = list(customNextItem=customNextItem))
summary(res)
# equivalent to the following
res2 <- mirtCAT(df, mod, local_pattern=pat, start_item = 'MI',
criteria = 'MI', design = list(max_items = 10))
summary(res2)
}
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