| Name : R-mirtjml
| |
| Version : 1.4.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.3.14
| Date : 2024-09-12 10:44:11
|
| Group : Development/Libraries/Other
| Source RPM : R-mirtjml-1.4.0-lp153.3.14.src.rpm
|
| Size : 0.34 MB
| |
| Packager : (none)
| |
| Summary : Joint Maximum Likelihood Estimation for High-Dimensional Item Factor Analysis
|
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.
< 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>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
