Identify treatment effect patterns for personalised decisions. (arXiv:1906.06080v2 [stat.ME] UPDATED)

In personalised decision making, evidence is required to determine whether an
action (treatment) is suitable for an individual. Such evidence can be obtained
by modelling treatment effect heterogeneity in subgroups. The existing
interpretable modelling methods take a top-down approach to search for
subgroups with heterogeneous treatment effects and they may miss the most
specific and relevant context for an individual. In this paper, we design a
\emph{Treatment effect pattern (TEP)} to represent treatment effect
heterogeneity in data. To achieve an …

arxiv decisions identify patterns treatment