This report presents guidelines for addressing the multiple comparisons problem in impact evaluations in the education area. The problem occurs due to the large number of hypothesis tests that are typically conducted across outcomes and subgroups in these studies, which can lead to spurious statistically significant impact findings. The guidelines, which balance type I and type II errors, involve specifying confirmatory and exploratory analyses in the study protocols, structuring the data by delineating outcome domains, conducting t-tests on composite domain outcomes, and applying multiplicity correction procedures to composites across domains. Guidelines are discussed for subgroup analyses, designs with multiple treatment groups, power analyses, and reporting impact findings. The report also provides background for applying the guidelines, including a detailed discussion of the multiplicity problem, statistical solutions that are found in the literature, and weighting options for forming composite domain outcomes. Four appendixes include: (1) Panel Members Attending the Multiple Comparisons Meetings; (2) Introduction to Multiple Testing; (3) Weighting Options for Constructing Composite Domain Outcomes; and (4) The Bayesian Hypothesis Testing Framework. (Contains 5 tables.)