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Researchers are often interested in testing the hypothesis that the effects of treatments, interventions, and so on are negligibly small rather than testing the hypothesis that treatments have no effect whatsoever. A number of procedures for conducting such tests have been suggested but have yet to be widely adopted. In this article, simple methods of testing such minimum-effect hypotheses are illustrated in a variety of applications of the general linear model. Tables and computational routines that can be used in conjunction with the familiar F test to evaluate the hypothesis that the effects of treatments or interventions exceed some minimum level are also provided.

S.L. Martin and N.S. Raju (1992) proposed a procedure for setting the cutoff score that maximized the total utility of a selection program by including a continuous function of recruiting costs. In the present article, the authors comment on some limitations of Martin and Raju's approach and suggest a modified procedure that uses a step recruitment-cost function. The modified procedure has the flexibility of allowing variable combinations of recruiting sources in any order to maximize total dollar utility of the selection program. It is also suggested that researchers should work toward the goals of finding the optimal combination of recruiting sources and of developing a confidence interval around the final estimate of the number of applicants based on the estimated variability of labor supply. A working example of the modified procedure is discussed. (Reprinted by permission of the publisher.)