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Joint mixed-effects models for causal inference with longitudinal data
Causal inference with observational longitudinal data and time-varying exposures is complicated due to the potential for time-dependent confounding and unmeasured confounding. Most causal inference methods that handle time-dependent confounding rely on either the assumption of no unmeasured confound...
में बचाया:
| में प्रकाशित: | Stat Med |
|---|---|
| मुख्य लेखकों: | , |
| स्वरूप: | Artigo |
| भाषा: | Inglês |
| प्रकाशित: |
2017
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| विषय: | |
| ऑनलाइन पहुंच: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5799019/ https://ncbi.nlm.nih.gov/pubmed/29205454 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.7567 |
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