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Selection Bias with Outcome-dependent Sampling
被引:6
作者:
Sjolander, Arvid
[1
]
机构:
[1] Karolinska Inst, Dept Med Epidemiol & Biostat, Nobels Vag 12A, S-17177 Stockholm, Sweden
基金:
瑞典研究理事会;
关键词:
Causal diagrams;
Causality;
Counterfactual graphs;
Outcome-dependent sampling;
Selection bias;
CAUSAL INFERENCE;
DEFINITION;
ASSUMPTION;
BOUNDS;
D O I:
10.1097/EDE.0000000000001567
中图分类号:
R1 [预防医学、卫生学];
学科分类号:
1004 ;
120402 ;
摘要:
In a seminal paper, Hernan et al. 2004 provided a systematic classification of selection biases, for scenarios where the selection is a collider between the exposure and the outcome. Hernan 2017 discussed another scenario, where the selection is statistically independent of the exposure, but associated with the outcome through common causes. In this note, we extend the discussion to scenarios where the selection is directly influenced by the outcome, but not by the exposure. We discuss whether these types of outcome-dependent selections preserve the sharp causal null hypothesis, and whether or not they allow for estimation of causal effects in the selected sample and/or in the source population.
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页码:186 / 191
页数:6
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