Planned missing data designs allow researchers to increase the amount and quality of data collected in a single study. Unfortunately, the effect of planned missing data designs on power is not straightforward. Under certain conditions using a planned missing design will increase power, whereas in other situations using a planned missing design will decrease power. Thus, when designing a study utilizing planned missing data researchers need to perform a power analysis. In this article, we describe methods for power analysis and sample size determination for planned missing data designs using Monte Carlo simulations. We also describe a new, more efficient method of Monte Carlo power analysis, software that can be used in these approaches, and several examples of popular planned missing data designs.