There is a problem when a relatively simple analysis is changed into a complex one just because some of the information is missing. Louis showed how to estimate the standard deviation of maximum likelihood estimate (MLE) for a parameter θ using the missing information. In the meantime, the resampling method is one of the best methods to calculate the standard deviation of sample estimates. In this article, we define and compare the standard deviation of a parameter θ using complete data, incomplete data, and the EM algorithm. As an illustration, we analyze a data from Rao and compare all methods for estimating variability.