Combining Experimental and Observational Data for Identification of Long-Term Causal Effects. (arXiv:2201.10743v1 [stat.ME])

Web: http://arxiv.org/abs/2201.10743

We consider the task of estimating the causal effect of a treatment variable
on a long-term outcome variable using data from an observational domain and an
experimental domain. The observational data is assumed to be confounded and
hence without further assumptions, this dataset alone cannot be used for causal
inference. Also, only a short-term version of the primary outcome variable of
interest is observed in the experimental data, and hence, this dataset alone
cannot be used for causal inference either. …

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