A recent survey of simulation studies concluded that an overwhelming majority of papers do not report a rationale for the number of iterations carried out in Monte Carlo robustness (MCR) experiments. The survey suggested that researchers might benefit from adopting a hypothesis testing strategy in the planning and reporting of simulation studies. This paper presents a table of the number of iterations necessary to detect departures from a series of nominal Type I error rates based upon hypothesis testing logic. The table is indexed by effect size, by significance level, and by power level for the two-tailed test that a proportion equals some constant. An alternative approach based upon the construction of a confidence interval is discussed and dismissed. The MCR research design demands an adequate definition of robustness and a sufficient sample size to detect departures from that definition. (Author/TJH)