The practical usage of poly2dich() function

[Seongho Bae]

Hi, Phil.

I saw the new function what the poly2dich() when the someone wants convert polytomous item to comparable dichotomous item.

I want to know the practical usage of poly2dich function.

Is this appropriate usage of poly2dich?

> mirt(poly2dich(Science), 1, technical = list(NCYCLES = 1e+4))

Iteration: 3327, Log-Lik: -2666.398, Max-Change: 0.00010

Call:

mirt(data = poly2dich(Science), model = 1, technical = list(NCYCLES = 10000))

Full-information item factor analysis with 1 factor(s).

Converged within 1e-04 tolerance after 3327 EM iterations.

mirt version: 1.19.1 

M-step optimizer: BFGS 

EM acceleration: Ramsay

Number of rectangular quadrature: 61

Log-likelihood = -2666.398

AIC = 5396.796; AICc = 5402.679

BIC = 5523.877; SABIC = 5422.342

> 

Seongho

[Phil Chalmers]

It's more of a model-fitting diagnostic approach when polytomous items seem to misfit, and you want to fit spline IRT models to each category separately to understand where the functional form is causing the misfit. 

a <- matrix(c(.8,.4,.7, .8, .4, .7, 1, 1, 1, 1))

d <- matrix(rep(c(2.0,0.0,-1,-1.5),10), ncol=4, byrow=TRUE)

dat <- simdata(a,d,2000, itemtype = rep('graded', 10))

head(dat)

mod <- mirt(dat, 1)

itemfit(mod)

# say that item 9 was misfitting

dat2 <- poly2dich(dat, which.items = 9)

it <- c(rep('graded', 8), rep('spline', 5), 'graded')

mod2 <- mirt(dat2, 1, it)

plot(mod2, type = 'trace', which = 9:13)

Phil

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