Estimating causal effects of time-dependent exposures on a binary endpoint in a high-dimensional setting.
Background: Recently, the intervention calculus when the DAG is absent (IDA) method was developed to estimate lower bounds of causal effects from observational high-dimensional data. Originally it was introduced to assess the effect of baseline biomarkers which do not vary over time. However, in man...
| Publicado en: | BMC Medical Research Methodology Vol. 18; no. 1 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
BioMed Central
7/3/2018
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| Acceso en línea: | Ver este registro en EBSCOhost |