  Scientific theories can often be formulated using equality and order
constraints on the relative effects in a linear regression model. For example,
it may be expected that the effect of the first predictor is larger than the
effect of the second predictor, and the second predictor is expected to be
larger than the third predictor. The goal is then to test such expectations
against competing scientific expectations or theories. In this paper a simple
default Bayes factor test is proposed for testing multiple hypotheses with
equality and order constraints on the effects of interest. The proposed testing
criterion can be computed without requiring external prior information about
the expected effects before observing the data. The method is implemented in
R-package called `{\tt lmhyp}' which is freely downloadable and ready to use.
The usability of the method and software is illustrated using empirical
applications from the social and behavioral sciences.
