group.test {eba} | R Documentation |
Tests for group effects in EBA models.
group.test(groups, A = 1:I, s = rep(1/J, J))
groups |
a 3d array including one aggregated 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 |
The five tests are all based on likelihood ratios.
Overall
tests a 1-parameter poisson model against a saturated
poisson model.
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.
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.
tests |
a table displaying the likelihood ratio test statistics |
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)