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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. <doi:10.1007/s11336-018-9646-5>; 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, <doi:10.1080/01621459.2019.1635485>.
| Version: | 1.4.0 |
| Depends: | R (≥ 3.1) |
| Imports: | Rcpp (≥ 0.12.17), stats, GPArotation |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2020-06-08 |
| DOI: | 10.32614/CRAN.package.mirtjml |
| Author: | Siliang Zhang [aut, cre], Yunxiao Chen [aut], Xiaoou Li [aut] |
| Maintainer: | Siliang Zhang <zhangsiliang123 at gmail.com> |
| BugReports: | https://github.com/slzhang-fd/mirtjml/issues |
| License: | GPL-3 |
| URL: | https://github.com/slzhang-fd/mirtjml |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | mirtjml results |
| Reference manual: | mirtjml.pdf |
| Package source: | mirtjml_1.4.0.tar.gz |
| Windows binaries: | r-devel: mirtjml_1.4.0.zip, r-release: mirtjml_1.4.0.zip, r-oldrel: mirtjml_1.4.0.zip |
| macOS binaries: | r-release (arm64): mirtjml_1.4.0.tgz, r-oldrel (arm64): mirtjml_1.4.0.tgz, r-release (x86_64): mirtjml_1.4.0.tgz, r-oldrel (x86_64): mirtjml_1.4.0.tgz |
| Old sources: | mirtjml archive |
| Reverse imports: | mirtsvd |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.