bring.flexmirt: Import Item and Ability Parameters from IRT Software
In cswells1/MeasInv: Collection of Methods to Detect Dichotomous and Polytomous Differential Item Functioning (DIF)

Description Usage Arguments Details Value Sample Output Files of IRT software Note Author(s) References See Also Examples

View source: R/bring_output.R

These functions import item and/or ability parameters from BILOG-MG 3, PARSCALE 4, flexMIRT, and mirt (R package).

bring.flexmirt(file, type = c("par", "sco"), rePrm = TRUE, n.factor = 1)

bring.bilog(file, type = c("par", "sco"))

bring.parscale(file, type = c("par", "sco"))

bring.mirt(x)

`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.
`rePrm`	A logical value. If TRUE, the item intercept and logit of item guessing parameters are reparameterized into the item difficulty and item guessing parameters, respectively. To estimate the IRT linking coefficients in this package, the item difficulty and item guessing parameters must be used. 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`.

The bring.flexmirt was written by modifying the function read.flexmirt (Pritikin, 2018). The functions bring.bilog and bring.parscale were written by modifying the functions read.bilog and read.parscale (Weeks, 2017), 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 mutidimensional item and ability parameter estimates, this package only deals with unidimensional IRT linking and equating 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.

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.

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

Among the four output files, two are from PARSCALE 4 with a file extension of ".PAR" (i.e., "parscale_base.PAR" and "parscale_new.PAR") and the rest are from flexMIRT with a file extension of "-prm.txt" (i.e., "flexmirt_base-prm.txt" and "flexmirt_new-prm.txt").

For the four IRT software, the base and new test forms 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. In each test form, there are 15 common items and they are items 41, 42, 42, ..., 54, 55. The examples below show how to import those output files.

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 meta data in a test form (e.g., item parameters, number of categories, models). See preplink, test.info, or simdat for more details about the item meta data.

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 irtlink for more details about the parameterization of the (generalized) partial credit model.

Hwanggyu Lim hglim83@gmail.com

Cai, L. (2015). flexMIRT 3.0 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

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

irtlink

## example 1
## import the "-prm.txt" output file from flexMIRT
flex_base <- system.file("extdata", "flexmirt_base-prm.txt", package = "irteQ")
flex_new <- system.file("extdata", "flexmirt_new-prm.txt", package = "irteQ")
bring.flexmirt(file=flex_base, "par")$Group1$full_df
bring.flexmirt(file=flex_new, "par")$Group1$full_df

## example 2
## import the ".par" output file from PARSCALE
pscale_base <- system.file("extdata", "parscale_base.PAR", package = "irteQ")
pscale_new <- system.file("extdata", "parscale_new.PAR", package = "irteQ")
bring.parscale(file=pscale_base, "par")$full_df
bring.parscale(file=pscale_new, "par")$full_df