A Comparsion of Multiple Imputation Methods for Missing Covariate Values in Recurrent Event Data
Multiple imputation (MI) is a commonly used approach to impute missing data. This thesis studies missing covariates in recurrent event data, and discusses ways to include the survival outcomes in the imputation model. Some MI methods under consideration are the event indicator D combined with, respe...
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| Format: | Others |
| Language: | English |
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Uppsala universitet, Statistiska institutionen
2015
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-256602 |