MI应该只补观测的缺失值吧，怎么多出行，这意味着多出观测了

是的，不知道为什么会多出了很多观测

As my understanding:
The imputation in MI procedure includes many methods. The bottom line is to impute missing through introducing randomness (with a set of plausible values that represent the uncertainty about the right value to impute). That is, instead of using one dataset, you create a number of datasets (nimpute=). NIMPUTE= default as 5. Of course, you need to adjust this randomness by using MIANALYZE procedure to summarize your analysis results.
In fact, if the results from the incomplete dataset (original) and the imputed dataset differ a lot, it is a big warning to review your imputation methods.
Jingju

实在抱歉，我从没用过这个PROC，我如果发现什么再跟你交流吧