Simulated Data for fitting a 3PL and 3PLu
Simulated responses of 10000 persons to 10 dichotomous items under two different simulation conditions.
data("Sim3PL", package = "psychotools")A data frame containing 10000 observations on 2 variables.
Item response matrix with 10 items (see details below).
Item response matrix with 10 items (see details below).
Data were simulated under the 3PL (resp) and 3PLu (resp2) (see
plmodel). For the 3PL scenario, the random number generator's
seed was set to 277. For the 3PLu scenario, the random number generator's seed
was set to 167. Person parameters θ_{i} of 10000 persons were drawn
from the standard normal distribution. Item difficulties b_{j} of 10
items (under the classical IRT parametrization) were drawn from the standard
normal distribution. Item discrimination parameters a_{j} were drawn
from a log-normal distribution with a mean of 0 and a variance of
0.0625 on the log scale. For the 3PL, guessing parameters
g_{j} were drawn from a uniform distribution with a lower limit of
0.1 and an upper limit of 0.2. For the 3PLu, upper asymptote
parameters u_{j} were drawn from a uniform distribution with a lower
limit of 0.8 and an upper limit of 0.9. In both scenarios, a
10000 x 10 matrix based on realizations of a uniform distribution
with a lower limit of 0 and an upper limit of 1 was generated and
compared to a 10000 x 10 matrix based on the probability function
under the respective model. If the probability of person i solving item
j exceeded the corresponding realization of the uniform distribution,
this cell of the matrix was set to 1, e.g., person i solved item
j.
## overview
data("Sim3PL", package = "psychotools")
str(Sim3PL)
## data generation
M <- 10000
N <- 10
## 3PL scenario
set.seed(277)
theta <- rnorm(M, 0, 1)
a <- rlnorm(N, 0, 0.25)
b <- rnorm(N, 0, 1)
g <- runif(N, 0.1, 0.2)
u <- rep(1, N)
probs <- matrix(g, M, N, byrow = TRUE) + matrix(u - g, M, N, byrow = TRUE) *
plogis(matrix(a, M, N, byrow = TRUE) * outer(theta, b, "-"))
resp <- (probs > matrix(runif(M * N, 0, 1), M, N)) + 0
all.equal(resp, Sim3PL$resp, check.attributes = FALSE)
## 3PLu scenario
set.seed(167)
theta <- rnorm(M, 0, 1)
a <- rlnorm(N, 0, 0.25)
b <- rnorm(N, 0, 1)
g <- rep(0, N)
u <- runif(N, 0.8, 0.9)
probs <- matrix(g, M, N, byrow = TRUE) + matrix(u - g, M, N, byrow = TRUE) *
plogis(matrix(a, M, N, byrow = TRUE) * outer(theta, b, "-"))
resp2 <- (probs > matrix(runif(M * N, 0, 1), M, N)) + 0
all.equal(resp2, Sim3PL$resp2, check.attributes = FALSE)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.