sim_4pl {PP} | R Documentation |
This function returns a dichotomous matrix of simulated responses under given item and person parameters.
sim_4pl(beta, alpha, lowerA, upperA, theta)
beta |
A numeric vector which contains the difficulty parameters for each item. |
alpha |
A numeric vector, which contains the slope parameters for each item. |
lowerA |
A numeric vector, which contains the lower asymptote parameters (kind of guessing parameter) for each item. |
upperA |
numeric vector, which contains the upper asymptote parameters for each item. |
theta |
A numeric vector which contains person parameters. |
Manuel Reif
################# simulate 4PL ############################################### set.seed(1700) # simulate 1-PL model ---------- thetas <- c(0.231,-1.313,1.772,1.601,1.733,-2.001,0.443,3.111,-4.156) sl <- c(1,1.1,0.9,0.89,1.5,1.1,1) la <- c(0,0,0.2,0.15,0.04,0,0.21) ua <- c(0.9,0.98,0.97,1,1,1,0.97) simdat1pl <- sim_4pl(beta=seq(-4,4,length.out=7), alpha=rep(1,7), lowerA=rep(0,7), upperA=rep(1,7), theta=thetas) head(simdat1pl) # simulate 2-PL model ---------- simdat2pl <- sim_4pl(beta=seq(-4,4,length.out=7), alpha=sl, lowerA=rep(0,7), upperA=rep(1,7), theta=thetas) head(simdat2pl) # simulate 3-PL model ---------- simdat3pl <- sim_4pl(beta=seq(-4,4,length.out=7), alpha=sl, lowerA=la, upperA=rep(1,7), theta=thetas) head(simdat3pl) # simulate 4-PL model ---------- simdat4pl <- sim_4pl(beta=seq(-4,4,length.out=7), alpha=sl, lowerA=la, upperA=ua, theta=thetas) head(simdat4pl)