Bayesian nonparametric analysis of longitudinal data with non-ignorable non-monotone missingness
In longitudinal studies, outcomes are measured repeatedly over time, but in reality clinical studies are full of missing data points of monotone and non-monotone nature. Often this missingness is related to the unobserved data so that it is non-ignorable. In such context, pattern-mixture model (PMM...
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| Format: | Others |
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VCU Scholars Compass
2019
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| Online Access: | https://scholarscompass.vcu.edu/etd/5750 https://scholarscompass.vcu.edu/cgi/viewcontent.cgi?article=6839&context=etd |