gen4PMData | R Documentation |
Generate item response data for or 1, 2, 3 or 4-parameter IRT Models.
gen4PMData(
NSubj = NULL,
abcdParams,
D = 1.702,
seed = NULL,
theta = NULL,
thetaMN = 0,
thetaVar = 1
)
NSubj |
the desired number of subject response vectors. |
abcdParams |
a p(items)-by-4 matrix of IRT item parameters: a = discrimination, b = difficulty, c = lower asymptote, and d = upper asymptote. |
D |
Scaling constant to place the IRF on the normal ogive or logistic metric. Default = 1.702 (normal ogive metric) |
seed |
Optional seed for the random number generator. |
theta |
Optional vector of latent trait scores. If theta = NULL (the default value) then gen4PMData will simulate theta from a normal distribution. |
thetaMN |
Mean of simulated theta distribution. Default = 0. |
thetaVar |
Variance of simulated theta distribution. Default = 1 |
data |
N(subject)-by-p(items) matrix of item response data. |
theta |
Latent trait scores. |
seed |
Value of the random number seed. |
Niels Waller
## Generate simulated 4PM data for 2,000 subjects
# 4PM Item parameters from MMPI-A CYN scale
Params<-matrix(c(1.41, -0.79, .01, .98, #1
1.19, -0.81, .02, .96, #2
0.79, -1.11, .05, .94, #3
0.94, -0.53, .02, .93, #4
0.90, -1.02, .04, .95, #5
1.00, -0.21, .02, .84, #6
1.05, -0.27, .02, .97, #7
0.90, -0.75, .04, .73, #8
0.80, -1.42, .06, .98, #9
0.71, 0.13, .05, .94, #10
1.01, -0.14, .02, .81, #11
0.63, 0.18, .18, .97, #12
0.68, 0.18, .02, .87, #13
0.60, -0.14, .09, .96, #14
0.85, -0.71, .04, .99, #15
0.83, -0.07, .05, .97, #16
0.86, -0.36, .03, .95, #17
0.66, -0.64, .04, .77, #18
0.60, 0.52, .04, .94, #19
0.90, -0.06, .02, .96, #20
0.62, -0.47, .05, .86, #21
0.57, 0.13, .06, .93, #22
0.77, -0.43, .04, .97),23,4, byrow=TRUE)
data <- gen4PMData(NSubj=2000, abcdParams = Params, D = 1.702,
seed = 123, thetaMN = 0, thetaVar = 1)$data
cat("\nClassical item difficulties for simulated data")
print( round( apply(data,2,mean),2) )
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