bring.flexmirt {irtQ} | R Documentation |
Import Item and Ability Parameters from IRT Software
Description
These functions import item and/or ability parameters from BILOG-MG 3, PARSCALE 4, flexMIRT, and the mirt R package.
Usage
bring.flexmirt(
file,
type = c("par", "sco"),
rePar = TRUE,
rePar.gpc = TRUE,
n.factor = 1
)
bring.bilog(file, type = c("par", "sco"))
bring.parscale(file, type = c("par", "sco"))
bring.mirt(x)
Arguments
file |
A file name (including the full path) containing the item or ability parameter estimates. |
type |
A character string indicating the type of output file. Available
options are |
rePar |
Logical. If |
rePar.gpc |
Logical. If |
n.factor |
A numeric value indicating the number of latent traits (factors)
estimated. This argument must be specified when |
x |
An object returned by the function |
Details
The bring.flexmirt()
function was developed by modifying
the read.flexmirt()
function (Pritikin & Falk, 2020). Similarly,
bring.bilog()
and bring.parscale()
were based on modified
versions of the read.bilog()
and read.parscale()
functions
(Weeks, 2010), respectively.
The supported file extensions for item and ability parameter files are: ".par" and ".sco" for BILOG-MG and PARSCALE, and "-prm.txt" and "-sco.txt" for flexMIRT. For mirt, the user provides the object name directly.
Although bring.flexmirt()
can extract multidimensional item and
ability parameter estimates, the irtQ package is designed exclusively
for unidimensional IRT applications.
For polytomous items, both bring.flexmirt()
and
bring.mirt()
can import item parameters for the graded response
model (GRM) and the generalized partial credit model (GPCM).
Value
These functions return a list containing several components. For flexMIRT output files, results from multiple-group analyses can be handled; in such cases, each list element corresponds to the estimation results for a separate group.
Sample Output Files of IRT software
To illustrate how to import item parameter estimate files from PARSCALE 4
and flexMIRT using bring.parscale()
and bring.flexmirt()
,
two example output files are included in this package.
One file is from PARSCALE 4 with a ".PAR" extension (i.e., "parscale_sample.PAR"), and the other is from flexMIRT with a "-prm.txt" extension (i.e., "flexmirt_sample-prm.txt").
Both files contain item parameter estimates from a mixed-format test with 55 items: fifty dichotomous items following the 3PL model and five polytomous items with five response categories modeled using the graded response model (GRM). The examples below demonstrate how to import these output files.
Note
For item parameter files from any IRT software, only the internal object
"full_df"
in the returned list is required for various functions in
the irtQ package. This object is a data frame containing item metadata
(e.g., item parameters, number of categories, IRT model types).
See info()
or simdat()
for more details on item metadata.
In addition, when item parameters are estimated using the partial credit
model (PCM) or the generalized partial credit model (GPCM), item step
parameters are included in the "full_df"
object. These step parameters
are calculated by subtracting the category threshold parameters from the
overall item difficulty (or location) parameter.
See the IRT Models section in irtQ-package for further
details on the parameterization of the GPCM.
Author(s)
Hwanggyu Lim hglim83@gmail.com
References
Cai, L. (2017). flexMIRT 3.5 Flexible multilevel multidimensional item analysis and test scoring (Computer software). Chapel Hill, NC: Vector Psychometric Group.
Chalmers, R. P. (2012). mirt: A multidimensional item response theory package for the R environment. Journal of Statistical Software, 48(6), 1-29.
Weeks, J. P. (2010). plink: An R Package for Linking Mixed-Format Tests Using IRT-Based Methods. Journal of Statistical Software, 35(12), 1-33. URL http://www.jstatsoft.org/v35/i12/.
Pritikin, J. (2018). rpf: Response Probability Functions. R package version 0.59. https://CRAN.R-project.org/package=rpf.
Pritikin, J. N., & Falk, C. F. (2020). OpenMx: A modular research environment for item response theory method development. Applied Psychological Measurement, 44(7-8), 561-562.
Muraki, E. & Bock, R. D. (2003). PARSCALE 4: IRT item analysis and test scoring for rating scale data (Computer Software). Chicago, IL: Scientific Software International. URL http://www.ssicentral.com
Zimowski, M. F., Muraki, E., Mislevy, R. J., & Bock, R. D. (2003). BILOG-MG 3: Multiple-group IRT analysis and test maintenance for binary items (Computer Software). Chicago, IL: Scientific Software International. URL http://www.ssicentral.com
See Also
Examples
## Example 1
# Import the "-prm.txt" output file from flexMIRT
flex_sam <- system.file("extdata", "flexmirt_sample-prm.txt", package = "irtQ")
# Read item parameters and convert them to item metadata
bring.flexmirt(file = flex_sam, "par")$Group1$full_df
## Example 2
# Import the ".PAR" output file from PARSCALE
pscale_sam <- system.file("extdata", "parscale_sample.PAR", package = "irtQ")
# Read item parameters and convert them to item metadata
bring.parscale(file = pscale_sam, "par")$full_df