Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical moderator. Drawing on work that addresses related, simpler problems and special cases of cluster-robust variance estimation, the authors develop three small-sample tests based on different approximations to the distribution of a robust Wald test statistic. In the remainder of the study, the authors describe their modeling assumptions, proposed tests, and some initial simulation result. These approximations are drawn from a wide array of areas within statistics, ranging from econometrics to survey sampling. The paper presents both new analytic work describing these small-sample corrected test statistics and the results of a large simulation study that compares these potential solutions, as well as a discussion of the implications of our findings for practice. Tables and figures are appended.