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Causal inference methods for combining randomized trials and observational studies: a review
With increasing data availability, treatment causal effects can be evalu...
11/16/2020 ∙ by Bénédicte Colnet, et al. ∙
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MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models
Inferring causal effects of a treatment, intervention or policy from obs...
02/25/2020 ∙ by Imke Mayer, et al. ∙
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Doubly robust treatment effect estimation with missing attributes
Missing attributes are ubiquitous in causal inference, as they are in mo...
10/23/2019 ∙ by Imke Mayer, et al. ∙
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R-miss-tastic: a unified platform for missing values methods and workflows
Missing values are unavoidable when working with data. Their occurrence ...
08/13/2019 ∙ by Imke Mayer, et al. ∙
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