Unified Framework for Computer Adaptive Testing Simulations

Documentation for package ‘meow’ version 1.0.0

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.