Estimating Causal Effects from Nonparanormal Observational Data
نویسندگان
چکیده
منابع مشابه
Estimating complex causal effects from incomplete observational data
Causal calculus is a tool to express causal effects in the terms of observational probability distributions. The application of causal calculus in the non-parametric form requires only the knowledge of the causal structure. However, some kind of explicit modeling is needed when numeric estimates of the causal effect are to be calculated. In this paper, the estimation of complicated nonlinear ca...
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Randomized control trials have long been considered the gold standard for establishing causal treatment effects. Can causal effects be reasonably estimated from observational data too? In observational studies, you observe treatment T and outcome Y without controlling confounding variables that might explain the observed associations between T and Y. Estimating the causal effect of the treatmen...
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In ideal randomised experiments, association is causation: association measures can be interpreted as effect measures because randomisation ensures that the exposed and the unexposed are exchangeable. On the other hand, in observational studies, association is not generally causation: association measures cannot be interpreted as effect measures because the exposed and the unexposed are not gen...
متن کاملPaper SAS374-2017: Estimating Causal Effects from Observational Data with the CAUSALTRT Procedure
Randomized control trials have long been considered the gold standard for establishing causal treatment effects. Can causal effects be reasonably estimated from observational data too? In observational studies, you observe treatment T and outcome Y without controlling confounding variables that might explain the observed associations between T and Y. Estimating the causal effect of the treatmen...
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When experimental designs are infeasible, researchers must resort to the use of observational data from surveys, censuses, and administrative records. Because assignment to the independent variables of observational data is usually nonrandom, the challenge of estimating causal effects with observational data can be formidable. In this chapter, we review the large literature produced primarily b...
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ژورنال
عنوان ژورنال: The International Journal of Biostatistics
سال: 2018
ISSN: 1557-4679
DOI: 10.1515/ijb-2018-0030