Crossover interference is now known to exist in humans but to date has been ignored in routine genetic mapping because of the computational burden involved. In a recent paper by Weeks et al. [Hum Hered 1993;43:86-97], interference was accounted for by the use of a variety of multilocus feasible map functions and a crossover model of Goldgar and Fain [Am J Hum Genet 1988;43:38-45]. In this paper, we present an alternative approach to incorporating crossover interference into multilocus likelihood computation, by modelling the underlying chiasma process directly using the chi 2 model, supplemented by an assumption of no chromatid interference. This procedure was applied to the same CEPH consortium chromosome 10 data set that was analyzed by Weeks et al. A fit to the data was achieved which was significantly better than that offered by the no-interference model, and comparable to the best of the alternatives considered by Weeks et al. We briefly discuss the relative merits of the different models for interference.