Simulate Data under a Generalized Partial Credit Model
rgpcm simulates IRT data under a generalized partial credit model.
rgpcm(theta, a, b, nullcats = FALSE, return_setting = TRUE)
theta |
numeric vector of person parameters. Can also be a list, then a
list of length |
a |
list of numerics of item discrimination parameters. |
b |
list of numeric vectors of item threshold parameters. |
nullcats |
logical. Should null categories be allowed? |
return_setting |
logical. Should a list containing slots of "a", "b", and "theta", as well as the simulated data matrix "data" be returned (default) or only the simulated data matrix? |
rgpcm returns either a list of the following components:
a |
list of numerics of item discrimination parameters used, |
b |
list of numeric vectors of item threshold parameters used, |
theta |
numeric vector of person parameters used, |
data |
numeric matrix containing the simulated data, |
or (if return_setting = FALSE) only the numeric matrix containing the
simulated data.
set.seed(1) ## item responses under a GPCM (generalized partial credit model) from ## 6 persons with three different person parameters ## 8 items with different combinations of two or three threshold parameters ## and corresponding discrimination parameters ppar <- rep(-1:1, each = 2) tpar <- rep(list(-2:0, -1:1, 0:1, 0:2), each = 2) dpar <- rep(list(1, 2), each = 4) sim <- rgpcm(theta = ppar, a = dpar, b = tpar) ## simulated item response data along with setting parameters sim ## print and plot corresponding item response object iresp <- itemresp(sim$data) iresp plot(iresp)
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