  The ICH E9 addendum introduces the term intercurrent event to refer to events
that happen after randomisation and that can either preclude observation of the
outcome of interest or affect its interpretation. It proposes five strategies
for handling intercurrent events to form an estimand but does not suggest
statistical methods for estimation. In this paper we focus on the hypothetical
strategy, where the treatment effect is defined under the hypothetical scenario
in which the intercurrent event is prevented. For its estimation, we consider
causal inference and missing data methods. We establish that certain 'causal
inference estimators' are identical to certain 'missing data estimators'. These
links may help those familiar with one set of methods but not the other.
Moreover, using potential outcome notation allows us to state more clearly the
assumptions on which missing data methods rely to estimate hypothetical
estimands. This helps to indicate whether estimating a hypothetical estimand is
reasonable, and what data should be used in the analysis. We show that
hypothetical estimands can be estimated by exploiting data after intercurrent
event occurrence, which is typically not used. We also present Monte Carlo
simulations that illustrate the implementation and performance of the methods
in different settings.
