Package: immer 1.6-1
immer: Item Response Models for Multiple Ratings
Implements some item response models for multiple ratings, including the hierarchical rater model, conditional maximum likelihood estimation of linear logistic partial credit model and a wrapper function to the commercial FACETS program. See Robitzsch and Steinfeld (2018) for a description of the functionality of the package. See Wang, Su and Qiu (2014; <doi:10.1111/jedm.12045>) for an overview of modeling alternatives.
Authors:
immer_1.6-1.tar.gz
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immer_1.6-1.tgz(r-4.4-emscripten)immer_1.6-1.tgz(r-4.3-emscripten)
immer.pdf |immer.html✨
immer/json (API)
NEWS
# Install 'immer' in R: |
install.packages('immer', repos = c('https://alexanderrobitzsch.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/alexanderrobitzsch/immer/issues
- data.immer01a - Some Example Datasets for the 'immer' Package
- data.immer01b - Some Example Datasets for the 'immer' Package
- data.immer02 - Some Example Datasets for the 'immer' Package
- data.immer03 - Some Example Datasets for the 'immer' Package
- data.immer04a - Some Example Datasets for the 'immer' Package
- data.immer04b - Some Example Datasets for the 'immer' Package
- data.immer05 - Some Example Datasets for the 'immer' Package
- data.immer06 - Some Example Datasets for the 'immer' Package
- data.immer07 - Some Example Datasets for the 'immer' Package
- data.immer08 - Some Example Datasets for the 'immer' Package
- data.immer09 - Some Example Datasets for the 'immer' Package
- data.immer10 - Some Example Datasets for the 'immer' Package
- data.immer11 - Some Example Datasets for the 'immer' Package
- data.immer12 - Some Example Datasets for the 'immer' Package
- data.ptam1 - Example Datasets for Robitzsch and Steinfeld
- data.ptam2 - Example Datasets for Robitzsch and Steinfeld
- data.ptam3 - Example Datasets for Robitzsch and Steinfeld
- data.ptam4 - Example Datasets for Robitzsch and Steinfeld
- data.ptam4long - Example Datasets for Robitzsch and Steinfeld
- data.ptam4wide - Example Datasets for Robitzsch and Steinfeld
Last updated 6 months agofrom:9e252a93a0. Checks:OK: 1 NOTE: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Aug 18 2024 |
R-4.5-win-x86_64 | NOTE | Aug 18 2024 |
R-4.5-linux-x86_64 | NOTE | Aug 18 2024 |
R-4.4-win-x86_64 | NOTE | Aug 18 2024 |
R-4.4-mac-x86_64 | NOTE | Aug 18 2024 |
R-4.4-mac-aarch64 | NOTE | Aug 18 2024 |
R-4.3-win-x86_64 | NOTE | Aug 18 2024 |
R-4.3-mac-aarch64 | NOTE | Aug 18 2024 |
R-4.3-mac-x86_64 | NOTE | Jul 19 2024 |
Exports:immer_agree2immer_ccmlimmer_cmlimmer_create_design_matrix_formulaimmer_FACETSimmer_hrmimmer_hrm_simulateimmer_installimmer_jmlimmer_latent_regressionimmer_opcatimmer_proc_dataimmer_reshape_wideformatimmer_unique_patternslc2_agreementlogits2probsprobs2logits
Dependencies:admiscCDMcodalatticeMatrixmvtnormpbapplypbvpolycorpsychotoolsRcppRcppArmadillosirtTAM
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Item Response Models for Multiple Ratings | immer-package immer |
Some Example Datasets for the 'immer' Package | data.immer01a data.immer01b data.immer02 data.immer03 data.immer04a data.immer04b data.immer05 data.immer06 data.immer07 data.immer08 data.immer09 data.immer10 data.immer11 data.immer12 |
Example Datasets for Robitzsch and Steinfeld (2018) | data.ptam1 data.ptam2 data.ptam3 data.ptam4 data.ptam4long data.ptam4wide |
Agreement Statistics for 2 Raters | immer_agree2 summary.immer_agree2 |
Composite Conditional Maximum Likelihood Estimation for the Partial Credit Model with a Design Matrix for Item Parameters | coef.immer_ccml immer_ccml summary.immer_ccml vcov.immer_ccml |
Conditional Maximum Likelihood Estimation for the Linear Logistic Partial Credit Model | anova.immer_cml coef.immer_cml immer_cml logLik.immer_cml summary.immer_cml vcov.immer_cml |
Wrapper to FACDOS | immer_FACETS summary.immer_FACETS |
Hierarchical Rater Model (Patz et al., 2002) | anova.immer_hrm immer_hrm IRT.likelihood.immer_hrm IRT.posterior.immer_hrm logLik.immer_hrm plot.immer_hrm summary.immer_hrm |
Simulating the Hierarchical Rater Model (Patz et al., 2002) | immer_hrm_simulate |
Support for the installation of the DOS-version from FACETS | immer_install |
Joint Maximum Likelihood Estimation for the Partial Credit Model with a Design Matrix for Item Parameters and \varepsilon-Adjustment Bias Correction | immer_jml IRT.likelihood.immer_jml logLik.immer_jml summary.immer_jml |
Unidimensional Latent Regression | anova.immer_latent_regression coef.immer_latent_regression immer_latent_regression logLik.immer_latent_regression summary.immer_latent_regression vcov.immer_latent_regression |
Estimation of Integer Item Discriminations | immer_opcat |
Processing Datasets and Creating Design Matrices for Rating Data | immer_create_design_matrix_formula immer_proc_data |
Creating a Rating Dataset in Wide Format | immer_reshape_wideformat |
Extracts Unique Item Response Patterns | immer_unique_patterns |
A Latent Class Model for Agreement of Two Raters | anova.lc2_agreement lc2_agreement logLik.lc2_agreement summary.lc2_agreement |
Conversion of Probabilities into Logits | logits2probs probs2logits |