This is for how to teach statistics and/or R.  It is not for how to do
analyses.  There may be some IRT sources on the internet.  You should
search for them.


On Fri, Jun 28, 2019 at 1:47 AM hello <[email protected]> wrote:

> Hello Sir/ma’am
> I am snehali, doing IRT analysis for 2pl model.
> 1)I have data of 38 students with 40 questions.
> 2)I find value of theta(ability) of student
> Formula = ln(total_count/(1-total_count))
> At student level
> 3)difficulty of questions (item difficulty)
> Formula = ln(total_count/(1-total_count))
> 4)Find probability of Item difficulty by using following code
> function (items)
> {
>               ncases <- nrow(items)
>               item.mean <- colMeans(items, na.rm = TRUE)
>               item.mean[item.mean < (1/ncases)] <- 1/ncases
>               irt.item.diff.rasch <- log((1/item.mean) - 1)
> }
> 5)Now need to find item discrimination ,this is code from package psych
> and not understand value of x,diff,item.diff,theta,scores
>
>
> function (item.diff, theta, items)
> {
>               irt.item.discrim <- function(x, diff, theta, scores) {
>                            fit <- -1 * (log(scores/(1 + exp(x * (diff -
> theta))) +
>                                          (1 - scores)/(1 + exp(x * (theta
> - diff)))))
>                            mean(fit, na.rm = TRUE)
>               }
>               nitems <- length(item.diff)
>               discrim <- matrix(NaN, nitems, 2)
>               for (i in 1:nitems) {
>                            item.fit <- optimize(irt.item.discrim, c(-5,
> 5), diff = item.diff[i],
>                                          theta = theta, scores = items[,
> i])
>                            discrim[i, 1] <- item.fit$minimum
>                            discrim[i, 2] <- item.fit$objective
>               }
>               irt.discrim <- discrim
> }
> Your reply is very important it will be great help for me
>
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