R: Unified Framework for Computer Adaptive Testing Simulations

# Unified Framework for Computer Adaptive Testing Simulations

## Documentation for package ‘meow’ version 1.0.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

construct_adj_mat | Construct an item-pool adjacency matrix.
data_existing | Load data from existing files
data_simple_1pl | A default data generation function that simulates normally distributed respondent abilities and item difficulties
edge_weight_exponential | Alternative edge weight functions for network-based item selection
edge_weight_inverse | Alternative edge weight functions for network-based item selection
edge_weight_linear | Alternative edge weight functions for network-based item selection
edge_weight_negative_log | Alternative edge weight functions for network-based item selection
edge_weight_power | Alternative edge weight functions for network-based item selection
meow | Conduct a full CAT simulation.
meow_administered | Logical mask of administered items.
meow_long | Convert the matrix simulation state to a long data frame of responses.
select_max_dist | Item selection by network distance criterion.
select_max_dist_enhanced | Network-based item selection with configurable edge weights.
select_max_info | Item selection by maximum Fisher information.
select_random | Item selection by random draw from the remaining item bank.
select_restrict_rate | Maximum-information item selection with an exposure-rate cap.
select_sequential | Item selection by item id, simulating a fixed test form.
update_maths_garden | Elo-style updates of person and item parameters (Maths Garden).
update_prowise_learn | Elo-style updates with paired item comparisons (Prowise Learn).
update_theta_mle | Update person ability via maximum likelihood estimation.