Statistical conclusion validity is concerned with an integrated evaluation of statistical power, significance testing, and effect size. A lack of attention to the integrated argument occurs because of an emphasis on significance testing, a lack of knowledge, and a lack of motivation. This article has three objectives. First, the central logic of the statistical conclusion validity argument is explained. Following that, issues relating to the three components are reviewed. These issues include computations, multivariate extensions, and recommendations for practice. Increasing use of model-testing procedures in which the goal of the analysis is not to reject the null hypothesis is noted. Finally, conclusions are offered and research needs are discussed.