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This paper proposes such an approach which aims to produce well-adjusted estimates for a given research question, based on plausible DAGs consistent with the data at hand, combining prior knowledge and standard regression methods.
In this article, we propose an approach to adjustment-variable selection which aims to produce well-adjusted estimates for a given research question based on plausible DAGs which are also consistent with the data at hand, and to clearly communicate assumptions and uncertainties underlying the estimates in DAG format.
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All calculations were based on plausible values (Fig. 4).
A plausible botnet reasoning problem is to find the minimal number of most likely botnets based on Plausible Bot Graph that explain all related evidences with investigated hosts.
We found a number of relatively robust differences between the standard deviations based on original plausible values and those based on plausible values generated from the questionnaire rotation models.
Based on plausible attribution of coverage, how many lives were saved?
These formulas are based on plausible ideas and default parameters but minimal supporting data on whole mixtures.
We would then apply the modified combining rules by Rubin ([2003]) to pool statistics based on these plausible values.
Workflow model is based on a DAG.
The workflow modeling is based on a DAG with fixed transfer costs (edges).
Based on our DAG, all models included maternal age, maternal education, maternal race, marital status, depression, and maternal weight (kg).
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