trineq {eba} | R Documentation |
Checks if binary choice probabilities fulfill the trinary inequality.
trineq(M, A = 1:I)
M |
a square matrix or a data frame consisting of absolute choice frequencies; row stimuli are chosen over column stimuli |
A |
a list of vectors consisting of the stimulus aspects;
the default is |
For any triple of stimuli x, y, z
, the trinary inequality states
that, if P(x, y) > 1/2
and (xy)z
, then
R(x, y, z) > 1,
where R(x, y, z) = R(x, y) R(y, z) R(z, x)
,
R(x, y) = P(x, y)/P(y, x)
, and (xy)z
denotes that x
and
y
share at least one aspect that z
does not have
(Tversky and Sattath, 1979, p. 554).
inclusion.rule
checks if a family of aspect sets is
representable by a tree.
Results checking the trinary inequality.
n |
number of tests of the trinary inequality |
prop |
proportion of triples confirming the trinary inequality |
quant |
quantiles of |
n.tests |
number of transitivity tests performed |
chkdf |
data frame reporting |
Tversky, A., & Sattath, S. (1979). Preference trees. Psychological Review, 86, 542–573. doi: 10.1037/0033-295X.86.6.542
data(celebrities) # absolute choice frequencies
A <- list(c(1,10), c(2,10), c(3,10),
c(4,11), c(5,11), c(6,11),
c(7,12), c(8,12), c(9,12)) # the structure of aspects
trineq(celebrities, A) # check trinary inequality for tree A
trineq(celebrities, A)$chkdf # trinary inequality for each triple