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Breaking Changes
Convert rstan to be a suggested package to simplify the installation process. This means that the Bayesian imputation functionality will not be available by default. To use this feature, you will need to install rstan separately (#441)
Deprecated the seed argument to method_bayes() in favour of using the base set.seed() function (#431)
New Features
Added vignette on how to implement retrieved dropout models with time-varying intercurrent event (ICE) indicators (#414)
Added vignette on how to obtain frequentist and information-anchored inference with conditional mean imputation using rbmi (#406)
Added FAQ vignette including a statement on validation (#407#440)
Updates to lsmeans() for better consistency with the emmeans package (#412)
Renamed lsmeans(..., weights = "proportional") to lsmeans(..., weights = "counterfactual")to more accurately reflect the weights used in the calculation.
Added lsmeans(..., weights = "proportional_em") which provides consistent results with emmeans(..., weights = "proportional")
lsmeans(..., weights = "proportional") has been left in the package for backwards compatibility and is an alias for lsmeans(..., weights = "counterfactual") but now gives
a message prompting users to use either "proptional_em" or "counterfactual" instead.
Added support for parallel processing in the analyse() function (#370)
Added documentation clarifying potential false-positive warnings from rstan (#288)
Added support for all covariance structures supported by the mmrm package (#437)