Subtests Using Algorithmic Rummaging Techniques
Convert empirical to fixed objective.
Subtest construction using a brute-force approach
Compute the number of possible subtest combinations
Cross-Validate a Measurement Model
Generate an empirical objective function for item selection.
Extracting empirical objective functions for item selection
Generate a fixed objective function for item selection.
Subtest construction using a simple genetic algorithm
Generating heuristics for the use in STUART subtest construction
Data selection for holdout validation.
k-Folds Crossvalidation
Subtest construction using the Max-Min-Ant-System
Generate matrix-components for objective functions.
Generating random samples of Subtests
STUART: Subtests Using Algorithmic Rummaging Techniques
Construct subtests from a pool of items by using ant-colony-optimization, genetic algorithms, brute force, or random sampling. Schultze (2017) <doi:10.17169/refubium-622>.