1 citations · 1 across the 3 of their papers we have counts for
3 papers
Sensitivity analysis methods for outcome missingness using substantive-model-compatible multiple imputation and their application in causal inference
Jiaxin Zhang, S. Ghazaleh Dashti, John B. Carlin +3
When using multiple imputation (MI) for missing data, maintaining compatibility between the imputation model and substantive analysis is important for avoiding bias. For example, s…
Multiple imputation for longitudinal data: A tutorial
Rushani Wijesuriya, Margarita Moreno-Betancur, John B Carlin +3
Longitudinal studies are frequently used in medical research and involve collecting repeated measures on individuals over time. Observations from the same individual are invariably…
Recoverability and estimation of causal effects under typical multivariable missingness mechanisms
Jiaxin Zhang, S. Ghazaleh Dashti, John B. Carlin +2
In the context of missing data, the identifiability or "recoverability" of the average causal effect (ACE) depends on causal and missingness assumptions. The latter can be depicted…