Automatic Construction of Forced-Choice Tests

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Documentation for package ‘autoFC’ version 0.2.0.1001

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

build_scale_with_blueprint	Construct Forced-Choice Blocks Aligned with the Specifications in a Blueprint
build_TIRT_var_names	Build Variable Names for the Pairwise/Rank Responses in the TIRT Model
cal_block_energy	Calculation of Item Block "Energy"
cal_block_energy_with_iia	Calculation of Item Block "Energy" with IIAs Included
construct_blueprint	Build a Blueprint Data Frame for the Focal FC Scale
convert_to_TIRT_response	Convert the Latent Utility Values into Thurstonian IRT Pairwise/Rank Responses with Pre-Specified Block Design
empirical_reliability	Calculate the Empirical Reliability of the Latent Trait Scores, Following the Formula in Brown & Maydeu-Olivares (2018).
facfun	Function for Checking If All Items in a Vector Are Unique
fit_TIRT_model	Fit the Thurstonian IRT Model with Long Format Response Data
get_CFA_estimates	Conduct Confirmatory Factor Analysis (CFA) and Obtain Parameter Estimates
get_iia	Helper Function for Outputting IIA Characteristics of Each Block
get_simulation_matrices	Generate Simulated Person and Item Parameter Matrices for the Thurstonian IRT Model Based on Confirmatory Factor Analysis Results
get_TIRT_long_data	Convert the TIRT Pairwise/Rank Response Data into Long Format Compatible with the thurstonianIRT Package
HEXACO_example_data	Example HEXACO Response Data
make_random_block	Construction of Random Item Blocks
plot_scores	Scatter Plot for True vs Estimated Scores, True Score vs Absolute Error, etc.
predict_scores	Predict trait scores based on estimated model
RMSE_range	Calculate the Overall RMSE of the Trait Scores, or the RMSE in a Certain Trait Score Range
sa_pairing_generalized	Automatic Item Pairing Method in Forced-Choice Test Construction
triplet_block_info	Block Information for the Example Triplet Response Data
triplet_example_data	Example Triplet Response Data