half_split {mycaas} | R Documentation |
Questioning rule (half split)
Description
Rule to select the most informative item at each step of the assessment.
Usage
half_split(likelihood, states, beta, eta, Q_pool = NA)
Arguments
likelihood |
A vector of the likelihood distribution on the states in the structure. |
states |
A state-by-problem matrix representing the structure, where an element is one if the item is included in the state, and zero otherwise. |
beta |
Vector of careless error probabilities. |
eta |
Vector of lucky guess error probabilities. |
Q_pool |
A vector contains the pool of items for the assessment in this moment of the procedure. |
Value
The item that maximizes the information (for details see, Doignon and Falmagne, 2012).
References
Doignon, J.-P., & Falmagne, J.-C. (1999). Knowledge spaces. Berlin: Springer.
Examples
# Consider the knowledge space and the parameters used in Brancaccio,
# de Chiusole, Stefanutti (2023) in Example 1
states<-matrix(c( 0,0,0,0,0,
0,0,0,0,1,
0,0,1,0,1,
0,0,0,1,1,
0,0,1,1,1,
1,0,1,0,1,
0,1,0,1,1,
1,0,1,1,1,
0,1,1,1,1,
1,1,0,1,1,
1,1,1,1,1), byrow=TRUE, ncol=5)
beta <-c(.004,.03,.02,.01,.007)
eta <-c(5e-06, 5e-05, 4e-05,.007,.08)
likelihood <-c(0,0,0,0,0,1/3,0,1/3,0,0,1/3)
Q_pool <- c(2,4,5)
half_split(likelihood,states,beta,eta,Q_pool)
[Package mycaas version 0.0.1 Index]