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...
| Main Authors: | , |
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| Format: | Online |
| Language: | English |
| Published: |
Springer US
2013
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3787209/ |