To test a hypothesis, you compare the maximized likelihood of a submodel to the maximized likelihood of a general model. You form a submodel by restricting one or more parameters estimated in the general model. Or you may restrict a parameter by setting it equal to another parameter, such as equating two genotypic means to specify a dominance relationship. A submodel must always have a lower likelihood than the general model. If not, the maximum likelihood has not been obtained for the general model.
Investigators usually test hypotheses using a chi-square test.
The degrees of freedom for the test equals the difference in the number of parameters estimated in obtaining the two likelihoods. When a parameter maximizes on the boundary, the degrees of freedom is unclear.