The Performance of Multiple Imputation for Longitudinal Ordinal Data under MCAR and MAR Dropouts
碩士 === 淡江大學 === 統計學系碩士班 === 98 === Missing data are a common occurrence in longitudinal studies. Multiple imputation can be used to solve the problem of missing data. Since the current imputation methods are developed based on the normality, Demirtas and Hedeker (2008) proposed a multiple imputation...
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| Format: | Others |
| Language: | en_US |
| Published: |
2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/38793144371710525199 |