rbmi

Implements standard and reference based multiple imputation methods for continuous longitudinal endpoints (Gower-Page et al. (2022) doi:10.21105/joss.04251). In particular, this package supports deterministic conditional mean imputation and jackknifing as described in Wolbers et al. (2022) doi:10.1002/pst.2234, Bayesian multiple imputation as described in Carpenter et al. (2013) doi:10.1080/10543406.2013.834911, and bootstrapped maximum likelihood imputation as described in von Hippel and Bartlett (2021) doi:10.1214/20-STS793.

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