run.GGUM2004 {GGUM} | R Documentation |
Call 'GGUM2004' and import the estimated parameters into R
Description
run.GGUM2004
executes a previously exported 'GGUM2004'
command file (via function write.GGUM2004
). It returns
the execution time, the item parameter estimates, and the person parameter
estimates.
Usage
run.GGUM2004(
cmd.file = "cmd",
data.file = "data",
datacmd.dir = tempdir(),
prog.dir = "C:/GGUM2004",
precision = 4
)
Arguments
cmd.file |
A character string defining the name of the command file. No file extension is required. |
data.file |
A character string defining the name of the data file. No file extension is required. |
datacmd.dir |
A character string defining the path to the directory
where both the data file (identified by the |
prog.dir |
A character string defining the directory where 'GGUM2004' is installed (default: "C:/GGUM2004"). |
precision |
Number of decimal places of the results (default = 4). |
Value
run.GGUM2004
returns a list cointaning the following
components:
time |
The 'GGUM2004' execution time. |
alpha |
The estimated discrimination parameters (for GGUM). |
delta |
The estimated difficulty parameters. |
taus |
The estimated threshold parameters. |
SE |
The standard errors for the estimated item parameters. |
theta |
The estimated person parameters and their standard errors. |
Details
Function run.GGUM2004
runs internally both functions
read.item.GGUM2004
(to import the 'GGUM2004' item
estimates into R) and read.person.GGUM2004
(to import
the 'GGUM2004' person estimates into R).
By experience, we noticed that long directory paths (especially if spaces
are included) make 'GGUM2004' fail to execute with error
file not found
. Therefore, a good advice is to choose
datacmd.dir
and prog.dir
wisely (short paths, no spaces).
Observe that this function is optimized for the Windows operating system because 'GGUM2004' is a Windows program.
Author(s)
Sebastian Castro-Alvarez, secastroal@gmail.com
References
Roberts JS, Fang H, Cui W, Wang Y (2006). “GGUM2004: A Windows-Based Program to Estimate Parameters in the Generalized Graded Unfolding Model.” Applied Psychological Measurement, 30, 64-65.
Examples
## Not run:
# Generate data:
C <- c(3, 3, 3, 5, 5, 5)
I <- 6
gen <- GenData.GGUM(750, I, C, seed = 125)
# Export data to 'GGUM2004':
export.GGUM2004(gen$data)
# Write command file:
write.GGUM2004(I, C, model = "GGUM")
# Run 'GGUM2004':
res.GGUM2004 <- run.GGUM2004()
## End(Not run)