Computerized Adaptive Testing for Survey Research
Computerized Adaptive Testing Generalized Partial Credit Model
Computerized Adaptive Testing Graded Response Model
Likelihood of the Specified Response Set
Computerized Adaptive Testing Survey (catSurv) Object
Check if Stop and/or Override Rules are Met
The First Derivative of the Log-Likelihood
The Second Derivative of the Log-Likelihood
Standard Error of Ability Parameter Estimate
Estimate of the Respondent's Ability Parameter
Estimates of Ability Parameters for a Dataset of Response Profiles
Expected Kullback-Leibler Information
Expected Observed Information
Expected Posterior Variance
Fisher's Information
Fisher's Test Information
Convert JSON object to Cat object
Methods for Accessing Cat
Object Slots
Expected Kullback-Leibler Information, Weighted by Likelihood
Look Ahead to Select Next Item
Computerized Adaptive Testing Latent Trait Model
Make Tree of Possible Question Combinations
Observed Information
Find Answer Profile that Minimizes Bias
Plotting function for Cat object
Expected Kullback-Leibler Information, Weighted by the Prior
Evaluate the Prior Density Distribution at Position
Probability of Responses to a Question Item or the Left-Cumulative Pro...
Qualtrics AJAX Handler
Clean adaptive inventory responses from Qualtrics
Select Next Item
Methods for Setting Value(s) to Cat
Object Slots
Calculates Fisher Information under different adaptive battery specifi...
Simulate answer profiles given some true value of theta
Estimates theta under different adaptive battery specifications
Update Answer to Single Item
Convert Cat object to JSON
Computerized Adaptive Testing Birnbaum's Three Parameter Model
Provides methods of computerized adaptive testing for survey researchers. See Montgomery and Rossiter (2020) <doi:10.1093/jssam/smz027>. Includes functionality for data fit with the classic item response methods including the latent trait model, Birnbaum`s three parameter model, the graded response, and the generalized partial credit model. Additionally, includes several ability parameter estimation and item selection routines. During item selection, all calculations are done in compiled C++ code.