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A Cautious Note on Auxiliary Variables That Can Increase Bias in Missing Data Problems.Causal inference, probability theory, and graphical insights.Variance reduction in randomised trials by inverse probability weighting using the propensity scoreHealth Behaviors of Korean Gastric Cancer Survivors with Hypertension: A Propensity Analysis of KNHANES III-V (2005-2012).Inverse probability weighting to estimate causal effect of a singular phase in a multiphase randomized clinical trial for multiple myeloma.A review of covariate selection for non-experimental comparative effectiveness research.Comment on: Margolis et al. lack of Effectiveness of hyperbaric oxygen therapy for the treatment of diabetic foot ulcer and the prevention of amputation: a cohort study. Diabetes Care 2013;36:1961-1966.Structural Approach to Bias in Meta-analyses.Case-control matching: effects, misconceptions, and recommendations.Data-driven confounder selection via Markov and Bayesian networks.On model selection and model misspecification in causal inference.An introduction to causal inference.
P2860
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P2860
description
2009 nî lūn-bûn
@nan
2009年の論文
@ja
2009年学术文章
@wuu
2009年学术文章
@zh
2009年学术文章
@zh-cn
2009年学术文章
@zh-hans
2009年学术文章
@zh-my
2009年学术文章
@zh-sg
2009年學術文章
@yue
2009年學術文章
@zh-hant
name
Remarks on the method of propensity score.
@en
Remarks on the method of propensity score.
@nl
type
label
Remarks on the method of propensity score.
@en
Remarks on the method of propensity score.
@nl
prefLabel
Remarks on the method of propensity score.
@en
Remarks on the method of propensity score.
@nl
P356
P1476
Remarks on the method of propensity score.
@en
P304
1415-6; author reply 1420-3
P356
10.1002/SIM.3521
P407
P50
P577
2009-04-01T00:00:00Z