bring.flexmirt {irtQ}

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 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 a directory) containing the item or ability parameters.

type

A character string indicating a type of output file. Available types are "par" for a file containing item parameter estimates and "sco" for a file containing ability parameter estimates.

rePar

A logical value. If TRUE and when the IRT dichotomous model (e.g., 3PLM) or GRM is fit to data, the item intercept and logit of item guessing parameters are reparameterized into the item difficulty and item guessing parameters, respectively. Default is TRUE.

rePar.gpc

A logical value. If TRUE and when (G)PCM is fit to data, the nominal model parameters in the flexMIRT parameter output file are reparameterized into the (G)PCM slope/difficulty parameters. Default is TRUE.

n.factor

A numeric value indicating the number of estimated factors. This argument should be specified when type = "sco". Default is 1.

x

An output object obtained from the function mirt.

Details

The bring.flexmirt was written by modifying the function read.flexmirt (Pritikin & Falk, 2020). The functions bring.bilog and bring.parscale were written by modifying the functions read.bilog and read.parscale (Weeks, 2010), respectively.

The file extensions for item parameter and ability files, respectively, are: ".par" and ".sco" for BILOG-MG and PARSCALE, and "-prm.txt" and "-sco.txt" for flexMIRT. For mirt, the name of the output object is specified by the user.

Although bring.flexmirt is able to extract multidimensional item and ability parameter estimates, this package only deals with unidimensional IRT methods.

For polytomous item parameters, bring.flexmirt and bring.mirt are able to import the item parameters of the graded response model and the (generalized) partial credit model.

Value

These functions return a list including several objects. Only for the output of flexMIRT, the results of multiple group analysis can be returned. In that case, each element of the list contains the estimation results for each group.

Sample Output Files of IRT software

To illustrate how to import the item parameter estimate files of PARSCALE 4 and flexMIRT using bring.parscale and bring.flexmirt, two item parameter estimate output files are included in this package.

Among the two output files, one of them is from PARSCALE 4 with a file extension of ".PAR" (i.e., "parscale_sample.PAR") and another one is from flexMIRT with a file extension of "-prm.txt" (i.e., "flexmirt_sample-prm.txt").

For the two item parameter estimate output files, both are mixed-format tests with 55 items consisting of fifty dichotomous items following the IRT 3PL model and five polytomous items with five categories following the graded response model. The examples below show how to import those output files.

Note

Regarding the item parameter files for any IRT software, only the internal object "full_df" in the returned list is necessary for the IRT linking. The object "full_df" is a data frame containing the item metadata in a test form (e.g., item parameters, number of categories, models). See info or simdat for more details about the item metadata.

Also, when item parameters are estimated using the partial credit or the generalized partial credit model, item step parameters are returned in the object "full_df". Item step parameters are the overall item difficulty (or location) parameter subtracted by the difficulty (or threshold) parameter for each category. See irtfit for more details about the parameterization of the (generalized) partial credit model.

Author(s)

Hwanggyu Lim [e-mail]

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 Program]. 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 Program]. Chicago, IL: Scientific Software International. URL http://www.ssicentral.com

See Also

irtfit

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 transform them to item meta data
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 transform them to item meta data
bring.parscale(file=pscale_sam, "par")$full_df