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mirtjml
View on CRAN: Click
here
Download and install mirtjml package within the R console
Install from CRAN:
install.packages("mirtjml")
Install from Github:
library("remotes")
install_github("cran/mirtjml")
Install by package version:
library("remotes")
install_version("mirtjml", "1.4.0")
Attach the package and use:
library("mirtjml")
Maintained by
Siliang Zhang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-12-21
Latest Update: 2020-06-08
Description:
Provides constrained joint maximum likelihood estimation
algorithms for item factor analysis (IFA) based on multidimensional item response theory
models. So far, we provide functions for exploratory and confirmatory IFA based on the
multidimensional two parameter logistic (M2PL) model for binary response data. Comparing
with traditional estimation methods for IFA, the methods implemented in this package scale
better to data with large numbers of respondents, items, and latent factors. The computation
is facilitated by multiprocessing 'OpenMP' API. For more information, please refer to:
1. Chen, Y., Li, X., & Zhang, S. (2018). Joint Maximum Likelihood Estimation for
High-Dimensional Exploratory Item Factor Analysis. Psychometrika, 1-23.
;
2. Chen, Y., Li, X., & Zhang, S. (2019). Structured Latent Factor Analysis for Large-scale Data:
Identifiability, Estimability, and Their Implications. Journal of the American Statistical
Association, .
How to cite:
Siliang Zhang (2018). mirtjml: Joint Maximum Likelihood Estimation for High-Dimensional Item Factor Analysis. R package version 1.4.0, https://cran.r-project.org/web/packages/mirtjml. Accessed 22 Dec. 2024.
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Complete documentation for mirtjml
Functions, R codes and Examples using
the mirtjml R package
Some associated functions: data_sim . getMIRTthreads . mirtjml_conf . mirtjml_expr . setMIRTthreads .
Some associated R codes: RcppExports.R . data.R . mirtjml_conf.R . mirtjml_expr.R . utilities.R . zzz.R . Full mirtjml package functions and examples
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