erf | R Documentation |
Utility function to compute empirical response functions.
erf(theta, data, whichItem, min = -3, max = 3, Ncuts = 12)
theta |
Vector of estimated latent trait scores. |
data |
A matrix of binary item responses. |
whichItem |
Data for an erf will be generated for whichItem. |
min |
Default = -3. Minimum value of theta. |
max |
Default = 3. Maximum value of theta. |
Ncuts |
Number of score groups for erf. |
probs |
A vector (of length Ncuts) of bin response probabilities for the empirical response function. |
centers |
A vector of bin centers. |
Ni |
Bin sample sizes. |
se.p |
Standard errors of the estimated bin response probabilities. |
Niels Waller
NSubj <- 2000
#generate sample k=1 FMP data
b <- matrix(c(
#b0 b1 b2 b3 b4 b5 b6 b7 k
1.675, 1.974, -0.068, 0.053, 0, 0, 0, 0, 1,
1.550, 1.805, -0.230, 0.032, 0, 0, 0, 0, 1,
1.282, 1.063, -0.103, 0.003, 0, 0, 0, 0, 1,
0.704, 1.376, -0.107, 0.040, 0, 0, 0, 0, 1,
1.417, 1.413, 0.021, 0.000, 0, 0, 0, 0, 1,
-0.008, 1.349, -0.195, 0.144, 0, 0, 0, 0, 1,
0.512, 1.538, -0.089, 0.082, 0, 0, 0, 0, 1,
0.122, 0.601, -0.082, 0.119, 0, 0, 0, 0, 1,
1.801, 1.211, 0.015, 0.000, 0, 0, 0, 0, 1,
-0.207, 1.191, 0.066, 0.033, 0, 0, 0, 0, 1,
-0.215, 1.291, -0.087, 0.029, 0, 0, 0, 0, 1,
0.259, 0.875, 0.177, 0.072, 0, 0, 0, 0, 1,
-0.423, 0.942, 0.064, 0.094, 0, 0, 0, 0, 1,
0.113, 0.795, 0.124, 0.110, 0, 0, 0, 0, 1,
1.030, 1.525, 0.200, 0.076, 0, 0, 0, 0, 1,
0.140, 1.209, 0.082, 0.148, 0, 0, 0, 0, 1,
0.429, 1.480, -0.008, 0.061, 0, 0, 0, 0, 1,
0.089, 0.785, -0.065, 0.018, 0, 0, 0, 0, 1,
-0.516, 1.013, 0.016, 0.023, 0, 0, 0, 0, 1,
0.143, 1.315, -0.011, 0.136, 0, 0, 0, 0, 1,
0.347, 0.733, -0.121, 0.041, 0, 0, 0, 0, 1,
-0.074, 0.869, 0.013, 0.026, 0, 0, 0, 0, 1,
0.630, 1.484, -0.001, 0.000, 0, 0, 0, 0, 1),
nrow=23, ncol=9, byrow=TRUE)
theta <- rnorm(NSubj)
data<-genFMPData(NSubj = NSubj, bParam = b, theta = theta, seed = 345)$data
erfItem1 <- erf(theta, data, whichItem = 1, min = -3, max = 3, Ncuts = 12)
plot( erfItem1$centers, erfItem1$probs, type="b",
main="Empirical Response Function",
xlab = expression(theta),
ylab="Probability",
cex.lab=1.5)
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