Item tree analysis (ITA) on a set of binary responses.
ita(R, L =NULL, makeK =FALSE, search = c("local","global"))
Arguments
R: a subject-by-problem indicator matrix representing the responses.
L: the threshold of violations acceptable for the precedence relation. If NULL (default), an optimal threshold is searched for.
makeK: should the corresponding knowledge structure be returned?
search: local (default) or global threshold search.
Details
ITA seeks to establish a precedence relation among a set of binary items. For each pair of items (p,q), it counts how often p is not solved if q is solved, which constitutes a violation of the relation. ITA searches for a threshold L for the maximum number of violations consistent with a (transitive) precedence relation. Its attempts to minimize the total discrepancy between R and K.
See van Leeuwe (1974) and Schrepp (1999) for details.
Returns
An object of class ita having the following components: - K: the knowledge structure corresponding to the precedence relation.
discrepancy: the discrepancy between R and K (fit), between K and R (complexity), and their sum (total).
transitiveL: the vector of transitive thresholds.
searchL: either NULL or the method used for threshold search.
L: the selected or requested threshold.
P: the precedence matrix containing the number of violations.
I: the precedence relation as a logical incidence matrix at threshold L.
References
Schrepp, M. (1999). On the empirical construction of implications between bi-valued test items. Mathematical Social Sciences, 38 (3), 361--375. tools:::Rd_expr_doi("10.1016/S0165-4896(99)00025-6")
Van Leeuwe, J.F. (1974). Item tree analysis. Nederlands Tijdschrift voor de Psychologie en haar Grensgebieden, 29 (6), 475--483.
See Also
blim.
Examples
data(chess)ita(chess$R)# find (locally) optimal threshold Li <- ita(chess$R, L =6, makeK =TRUE)identical(sort(as.pattern(i$K)), sort(as.pattern(chess$dst1)))## Plotting the precedence relationif(requireNamespace("relations")&& requireNamespace("Rgraphviz")){ plot(relations::as.relation(i$I))}