Applications of the compatible conditional random variables on imputation methods

• Main Author: 曾琬甯
• Other Authors: 姜志銘
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/19683522265275652481

碩士 === 國立政治大學 === 應用數學研究所 === 99 === There are some available imputation methods to deal with missing data. However, whether imputation methods based on conditional distributions are effective is still questionable. Van Buuren et al.(2006) discuss two incompatible conditional distributions models (one conditional distribution has a linear relation, the other conditional distribution has a squared or a logarithmic relation). According to their simulation results, Van Buuren et al.(2006) conclude that imputation methods based on these two incompatible models are effective. In this thesis, we try to explain why the two imputation models are effective. In addition, we discuss whether all imputation methods based on incompatible models give estimated parameter values close to the true values. The simulation results of these methods are also tested statistically to answer this question. In conclusion, we find the answer is negative.