pattern
computes the absolute frequencies of the (occurring)
response patterns, and optionally, the absolute frequencies of a
collection of specified knowledge states in a dataset.
pattern(dataset, n = 5, P = NULL)
n = 5
, giving the
$n$ highest frequencies and their corresponding response
patterns to be returned.P = NULL
corresponds to no
knowledge states being specified.dataset
, n
, and P
are of
required types, pattern
returns a named list consisting of
the following three components:dataset
.dataset
. Each row represents a knowledge
state, the last column gives the frequencies of the states. If
P = NULL
, the component states
is NULL
.n
refers to response patterns, not knowledge states,
and in particular is independent of specifications of the argument
P
. If pattern
is called without specifying $n$
explicitly, the response patterns with the five highest frequencies
are returned (along with their frequencies). If $n$ is
specified, the response patterns with the $n$ highest
frequencies are returned (along with their frequencies). If $n$
is larger than the number of different response patterns in the
dataset, $n$ is set the number of different response patterns. The knowledge states are represented as $1$/$0$-patterns and
are the rows of the argument matrix P
. The matrix P
must contain only ones and zeros, which encode whether or not an
item belongs to a knowledge state, respectively. If P
is not
specified, pattern
only returns information about response
patterns (as described previously).
The data must contain only ones and zeros, which encode solving or failing to solve an item, respectively.
Uenlue, A. and Sargin, A. (2010) DAKS: An R package for data analysis methods in knowledge space theory. Journal of Statistical Software, 37(2), 1--31. URL http://www.jstatsoft.org/v37/i02/.
ob_counter
for computation of numbers of
counterexamples; simu
for data simulation tool;
iita
, the interface that provides the three inductive
item tree analysis methods under one umbrella. See also
DAKS-package
for general information about this
package.
pattern(pisa, n = 3)
pattern(pisa)
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