Informative censoring with an imprecise anchor event: estimation of change over time and implications for longitudinal data analysis
A number of methods have been developed to analyze longitudinal data with dropout. However, there is no uniformly accepted approach. Model performance, in terms of the bias and accuracy of the estimator, depends on the underlying missing data mechanism and it is unclear how existing methods will p...
| Main Author: | |
|---|---|
| Language: | en_US |
| Published: |
2016
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/2144/14316 |