Man pages for ForceChoice
Forced-Choice Modeling Based on Item Response Theory and Cognitive Diagnostic Models
| apply_rotation_promax | Apply factor rotation to discrimination matrix and latent... |
| build_stan_control | Build Stan sampling-control list from user-provided... |
| check_integer_scalar | Validate a scalar integer parameter |
| clip_prob | Clamp probabilities away from 0 and 1 |
| coef | S3 Methods: coef |
| compute_fcgdina_item_prob | Compute FCGDINA item-level endorsement probabilities |
| confint | S3 Methods: confint |
| deviance | S3 Methods: deviance |
| extract | S3 Methods: extract |
| extract_corr_stan | Extract correlation posterior summary from Stan MCMC output |
| extract_rhat_matrix | Extract R-hat values for a matrix parameter from a Stan... |
| extract_rhat_vector | Extract R-hat values for a vector parameter from a Stan... |
| extract_theta_stan | Extract theta posterior summary from Stan MCMC output |
| fit.FCDCM | Fit the Forced-Choice Diagnostic Classification Model (FCDCM) |
| fit.FCGDINA | Fit the Forced-Choice GDINA Model |
| fit.FCGGUM | Fit the Forced-Choice Generalized Graded Unfolding Model... |
| fit.FCMIRT | Fit the Forced-Choice Multidimensional IRT (FCMIRT) Model |
| fit.MGGUM | Fit the Multidimensional Generalized Graded Unfolding Model... |
| fit.MGPCM | Fit the Multidimensional Generalized Partial Credit Model... |
| fit.MIRT | Fit the Multidimensional Item Response Theory (MIRT) Model |
| fitted | S3 Methods: fitted |
| fit.TIRT | Fit the Thurstonian Item Response Theory (TIRT) Model |
| ForceChoice-package | ForceChoice: Forced-Choice Modeling Based on IRT and CDM |
| forced_choice_data_conversion | Forced-Choice Data Conversion Formats |
| forced_choice_from_agree | Compute forced-choice pattern probabilities from item... |
| free_corr_npar | Degrees of freedom for a correlation matrix |
| generate_fc_permutation_patterns | Generate forced-choice permutation patterns |
| generate_theta_mvn | Generate latent trait vectors from a multivariate normal... |
| get.block.items.from.data | Extract Block Items from Forced-Choice Data |
| get.block.items.from.data.FCDCM | Extract Block Items from FCDCM Data |
| get.data.from.response | Convert an Integer Response (Pattern-Index) Matrix to FC Data... |
| get.data.from.response.FCDCM | Convert an FCDCM Response Matrix to FC Data Strings |
| get.data.from.response.TIRT | Convert TIRT Pairwise-Response Matrix to Forced-Choice Data... |
| get_design_matrix_cdm | Build the CDM design matrix for a set of attribute patterns |
| get.fit.index | Goodness-of-Fit Indices for Fitted Models |
| get.log_lik | Extract pointwise log-likelihood matrix |
| get_precedent_patterns | Find precedent (subset) patterns for monotonicity enforcement |
| get.response.from.data | Convert FC Data Strings to an Integer Response... |
| get.response.from.data.FCDCM | Convert FCDCM Data Strings to a Binary Response Matrix |
| get.response.from.data.TIRT | Convert TIRT Forced-Choice Data to Pairwise-Response Matrix |
| good.of.fit | Goodness-of-Fit Indices for Latent Probability Models |
| logLik-class | Extract Log-Likelihood from Fitted Models |
| make_item_prob_cdm | Build CDM item response probabilities for attribute mastery... |
| make_quadrature_grid_mvn | Multivariate normal quadrature grid with Cholesky-stabilised... |
| mggum_par_free_mask | Free-parameter mask for MGGUM models |
| mgpcm_par_free_mask | Free-parameter mask for MGPCM models |
| mirt_par_free_mask | Free-parameter mask for MIRT models |
| model.FCDCM | Compute FCDCM Block Response Probabilities |
| model.FCGDINA | Compute FCGDINA forced-choice pattern probabilities |
| model.FCGGUM | Compute FCGGUM Forced-Choice Pattern Probabilities |
| model.FCMIRT | Compute FCMIRT Forced-Choice Pattern Probabilities |
| model.MGGUM | Compute MGGUM Category Response Probabilities |
| model.MGPCM | Compute MGPCM Category Response Probabilities |
| model.MIRT | Compute MIRT Item Response Probabilities |
| model.TIRT | Compute TIRT Pairwise Comparison Probabilities |
| model_type_to_int | Map resolved model name to integer code |
| nobs | S3 Methods: nobs |
| normalize_fc_type | Normalise and recycle forced-choice type vector |
| pattern_key | Convert binary matrix rows to string keys |
| plot | S3 Methods: plot |
| predict | S3 Methods: predict |
| S3 Methods: print | |
| residuals | S3 Methods: residuals |
| resolve_block_items | Auto-detect block.items from forced-choice ranking data |
| resolve_D | Resolve the number of latent dimensions |
| resolve_fc_blocks | Resolve forced-choice block and Q-matrix configuration |
| resolve_fc_type | Auto-detect forced-choice response type from data |
| resolve_model_type | Resolve IRT model type with alias support |
| restore_mcmc_env | Restore MCMC threading environment to its previous state |
| rotate | S3 Methods: rotate |
| sample_fc_responses | Sample forced-choice responses from block-level pattern... |
| setup_mcmc_env | Setup single-threaded MCMC environment |
| sim.data.FCDCM | Simulate Data from the Forced-Choice DCM Model |
| sim.data.FCGDINA | Simulate Forced-Choice GDINA Data |
| sim.data.FCGGUM | Simulate Data from the Forced-Choice GGUM Model |
| sim.data.FCMIRT | Simulate FCMIRT Data |
| sim.data.MGGUM | Simulate Data from the Multidimensional Generalized Graded... |
| sim.data.MGPCM | Simulate Data from the Multidimensional Generalized Partial... |
| sim.data.MIRT | Simulate Data from the Multidimensional IRT (MIRT) Model |
| sim.data.TIRT | Simulate Data from the Thurstonian IRT (TIRT) Model |
| summary | S3 Methods: summary |
| tirt_par_free_mask | Free-parameter mask for TIRT models |
| triplets | Triplets of Pairwise Comparisons |
| update | S3 Methods: update |
| validate_corr_matrix | Validate a user-supplied correlation matrix |
| vcov | S3 Methods: vcov |
