Graphical models for causation, and the identification problem.
about
Evaluating uncertainty to strengthen epidemiologic data for use in human health risk assessmentsA causal framework for surrogate endpoints with semi-competing risks data.Invited commentary: Can changes in the distributions of and associations between education and income bias estimates of temporal trends in health disparities?Causality, mediation and time: a dynamic viewpoint.Causal versus spurious spatial exposure-response associations in health risk analysis.Caveats for causal interpretations of linear regression coefficients for fine particulate (PM2.5) air pollution health effects.Improving causal inferences in risk analysis.Validating niche-construction theory through path analysis
P2860
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P2860
Graphical models for causation, and the identification problem.
description
2004 nî lūn-bûn
@nan
2004年の論文
@ja
2004年論文
@yue
2004年論文
@zh-hant
2004年論文
@zh-hk
2004年論文
@zh-mo
2004年論文
@zh-tw
2004年论文
@wuu
2004年论文
@zh
2004年论文
@zh-cn
name
Graphical models for causation, and the identification problem.
@ast
Graphical models for causation, and the identification problem.
@en
type
label
Graphical models for causation, and the identification problem.
@ast
Graphical models for causation, and the identification problem.
@en
prefLabel
Graphical models for causation, and the identification problem.
@ast
Graphical models for causation, and the identification problem.
@en
P2860
P356
P1433
P1476
Graphical models for causation, and the identification problem.
@en
P2093
David A Freedman
P2860
P304
P356
10.1177/0193841X04266432
P577
2004-08-01T00:00:00Z