Many imputation techniques and imputation software packages have been developed over the years to deal with missing data. Different methods may work well under different circumstances, and it is advisable to conduct a sensitivity analysis when choosing an imputation method for a particular survey. This study reviewed about 30 imputation methods and 5 imputation software packages. Eleven of the most popular imputation methods were evaluated through a Monte Carlo simulation study. The first four chapters of this report are methodology discussions based on a review of the literature on imputation. Chapter 1, describes about 30 commonly used methods, including those used by the National Center for Education Statistics, and discusses their strengths and weaknesses. Chapter 2 focuses on five software packages for imputation, Nonresponse bias correction through imputation is addressed in chapter 3, and variance estimation with imputed data and multiple imputation inference is discussed in chapter 4. Chapter 5 reports the results of the simulation study, which evaluated 11 methods according to 8 evaluation criteria for 4 types of distributions, 5 types of missing mechanisms, and 4 types of missing rates. (Contains 31 tables and 45 references.) (SLD)