Outcome regression methods in causal inference : The difference LASSO and selection of effect modifiers
In causal inference, a central aim of covariate selection is to provide a subset of covariates, that is sufficient for confounding adjustment. One approach for this is to construct a subset of covariates associated with the outcome. This is sometimes referred to as the outcome approach, which is the...
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| Format: | Others |
| Language: | English |
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Umeå universitet, Statistik
2018
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149423 |