Managing Nonignorable Missing Data with Clustered Multinomial Responses
博士 === 國立陽明大學 === 公共衛生研究所 === 103 === The problem of missing data is an important issue in statistical analysis. Not only the efficiency loss due to reduction of information, but also the validity of inferences may be challenged. If the data are not missing randomly, simply ignoring the missing...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
2015
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| Online Access: | http://ndltd.ncl.edu.tw/handle/90234493746773871732 |