a 3d array containing one aggregate choice matrix
per group
A
a list of vectors consisting of the stimulus aspects;
the default is 1:I, where I is the number of stimuli
s
the starting vector with default 1/J for all parameters,
where J is the number of parameters
Value
testsa table displaying the likelihood ratio test statistics
Details
The five tests are all based on likelihood ratios.
Overall compares a 1-parameter Poisson model to a saturated
Poisson model, thereby testing the equality of the frequencies in each cell
of the array. This test corresponds to simultaneously testing for a null
effect of (1) the context induced by a given pair, (2) the grouping factor,
(3) the stimuli, and (4) the imbalance between pairs. The deviances of
the remaining tests sum up to the total deviance associated with the overall
test.
EBA.g tests an EBA group model against a saturated
binomial group model, which corresponds to a goodness of fit test of
the EBA group model.
Group tests an EBA model for the pooled data against the EBA
group model, which corresponds to testing for group differences.
Effect tests an indifference model against the pooled EBA model,
which corresponds to testing for a stimulus effect.
Imbalance tests for differences in the number of observations
per pair by comparing the average sample size (1-parameter Poisson model)
to the actual sample sizes (saturated Poisson model).
See Duineveld, Arents, & King (2000) for details.
References
Duineveld, C.A.A., Arents, P., & King, B.M. (2000). Log-linear modelling of
paired comparison data from consumer tests.
Food Quality and Preference, 11, 63--70.
data(pork) # Is there a difference between Judge 1 and Judge 2?groups <- array(c(apply(pork[,,1:5], 1:2, sum),
apply(pork[,,6:10], 1:2, sum)), c(3,3,2))
group.test(groups)