Subjective probabilities play an important role in marketing
research, for example where individuals rate the likelihood that
they will purchase a new to develop product. The tau-equivalent
model can describe the joint behaviour of multiple test items
measuring the same subjective probability. It improves the
reliability of the subjective probability estimate by using a
weighted sum as the outcome of the test rather than an unweighted
sum. One can choose the weights to obtain maximal reliability.
In this paper we stress the use of confidence intervals to assess
maximal reliability, as this allows for a more critical assessment
of the items as measurement instruments. Furthermore, two new
confidence intervals for the maximal reliability are derived and
compared to intervals derived earlier in \\citet{YuanBentler2002,
RaykovPenev2006}. The comparison involves coverage curves, a
methodology that is new in the field of reliability. The existing
Yuan-Bentler and Raykov-Penev intervals are shown to overestimate
the maximal reliability, whereas one of our proposed intervals, the
stable interval, performs very well. This stable interval hardly
shows any bias, and has a coverage for the true value which is
approximately equal to the confidence level