This chapter considers hybrid methods in which empirical likelihood is combined with other methods. There are a number of problems where a parametric likelihood is known or trusted for part, but not all, of the problem. In those cases, hybrid methods fill in the gaps with empirical likelihood. Similarly, an empirical likelihood can be combined with a Bayesian prior distribution, the bootstrap, and various jackknives. Bootstrap calibration of empirical likelihood is discussed elsewhere (Chapters 3.3 and 5.6.), as is a hybrid between empirical likelihood and permutation tests (Chapter 10.3).