In analyses of patient survival it is often desirable to compare observed survival curves with expected survival curves based on information obtained from the general population. However, current methods of calculating expected survival curves are difficult to interpret and are often poorly documented. We discuss an alternative formulation of the so-called direct method which we recommend for general use. By simulation, we show that the expected survival curve obtained from this method represents the expectation of a Kaplan-Meier curve for a set of random population controls. Thus, the term expected survival does not refer to the expectation of patient survival, but rather to the expected survival curve for a random set of controls. The alternative methods are discussed, and we illustrate the methods in an analysis of long time survival of a population-based sample of peptic ulcer patients.