GGUM-package: GGUM

Description Details Author(s) References See Also Examples

Description

The GGUM package fits the generalized graded response model (GGUM; Roberts et al., 1996, 2000). It is based on marginal maximum likelihood (Roberts et al., 2000) to estimate the item parameters and an estimated a posteriori (EAP) method to estimate the person parameters.

The GGUM is defined by

P(Z_i = z|t_n) = ( f(z) + f(M-z) ) / (sum( f(w) + f(M - w); w = 0, ..., C )),

f(w) = exp( alpha_i ( w(t_n - delta_i) - sum( tau_ik; k = 0, ..., w) ) ),

where:

Parameter tau_i0 is arbitrarily constrained to zero and the threshold parameters are constrained to symmetry around zero, that is, tau_{i(C+1)} = 0 and tau_{iz} = -tau_{i(M-z+1)} for z != 0.

This package produces comparable results to the ones based on the GGUM2004 program (Roberts et al., 2000; Roberts et al., 2006), for the GUM (Model 3 in GGUM2004) and the GGUM (Model 8 in GGUM2004). For those accustomed to using GGUM2004, this packages provides a useful set of functions that allow exporting data and code to GGUM2004, running GGUM2004, and retrieving the parameter estimates. Thus, if desired, one can run GGUM2004 and retrieve the results completely from within the R environment.

Versions:

Details

Package: GGUM
Type: Package
Version: 0.4-3
Date: 2021-10-07
License: GPL Version 2 or later

The GGUM package contains useful functions, summarized below:

Author(s)

Maintainer: Jorge N. Tendeiro tendeiro@hiroshima-u.ac.jp

Authors:

References

\insertRef

RobertsLaughlin1996GGUM

\insertRef

Robertsetal2000GGUM

\insertRef

Robertsetal2006GGUM

See Also

Useful links:

Examples

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## Not run: 
# Example 1 - Same value C across items:
# Generate data:
gen1 <- GenData.GGUM(2000, 10, 2, seed = 125)
# Fit the GGUM:
fit1 <- GGUM(gen1$data, 2)
th1  <- Theta.EAP(fit1)
# Plot the test information function:
plotTIF(fit1, th1)
# Check model fit:
MOD.res <- MODFIT(fit1)

# Example 2 - Different C across items:
# Generate data:
set.seed(1); C <- sample(3:5, 10, replace = TRUE)
I <- 10
gen2 <- GenData.GGUM(2000, I, C, seed = 125)
# Fit the GGUM:
fit2 <- GGUM(gen2$data, C)
th2  <- Theta.EAP(fit2)
# Plot item information functions for items 1 and 3:
plotIIF(fit2, th2, items = c(1, 3))

# Example 3 - Fit GGUM using GGUM2004:
# Assuming the installation directory is C:/GGUM2004, then do this:
# Export data to GGUM2004:
export.GGUM2004(gen2$data)
# Write command file:
write.GGUM2004(I, C)
# Run GGUM2004:
res.GGUM2004 <- run.GGUM2004()

## End(Not run)

GGUM documentation built on Oct. 7, 2021, 5:07 p.m.