The density ratio model specifies that the loglikelihood ratio of two unknown densities is of known linear form which depends on some finite dimensional parameters. The model can be broadened to allow for m-samples in a quite natural way. Estimation of both parametric and non- parametric part of the models is carried out by the method of empirical likelihood. We review some recent results about the density ratio model and show how it is utilized for the analysis of two or more samples. Meet the speaker in Room 212 Cockins Hall at 4:30 p.m. Refreshments will be served.