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Multiple Imputation of Missing Covariates in NONMEM and Evaluation of the Method’s Sensitivity to η-Shrinkage
Multiple imputation (MI) is an approach widely used in statistical analysis of incomplete data. However, its application to missing data problems in nonlinear mixed-effects modelling is limited. The objective was to implement a four-step MI method for handling missing covariate data in NONMEM and to...
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| Main Authors: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Springer US
2013
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3787209/ https://ncbi.nlm.nih.gov/pubmed/23868748 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1208/s12248-013-9508-0 |
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